#How STATA is Useful to Process The Information from Data

[nursingwriter]

Sundborg et al. (2012) conducted a quantitative study, which examined the preparedness of nurses to provide care for women who are exposed to intimate partner violence (p.1). The study was carried out on the premise that intimate partner violence (IPV) has significant effect on women's health. Therefore, nurses need adequate preparations to identify such victims and provide suitable interventions. While the study provides significant insights relating to nurses' preparedness in handling such patients, there are some drawbacks associated with it as demonstrated in this critique. The sample for this study was randomly selected from the 174 primary health care centers that employ approximately 1,200 active nurses in Stockholm County (Sundborg et al., 2012, p.3). Since the sample was selected randomly, a probability sampling method was utilized by the researchers. Every individual in the sampling population had equal chance of being included in the study. The results from this sampling method were representative of the population since random sampling enables extrapolation of findings to the whole population. This sampling method did not introduce any bias because every individual in the sample population had equal chances of being considered and every primary health care center (PHCC) in the county was contacted and invited to participate in the research. The sample size was identified through a randomization process in which each PHCC has a unique number written on a card and placed in a pot. This resulted in identifying an adequate sampling size that represented the entire population. The rights of participants were ensured through protection of privacy and confidentiality as well as liberty to withdraw at any time. However, the researchers did not clearly identify eligibility criteria and delimitations for participating in the study. Data Collection Data collection instruments for this study are clearly identified since the researchers utilized a questionnaire, which was reviewed and modified by Statistics Sweden, a professional survey designer. Given the nature of this research, the use of questionnaires that were distributed to the selected primary health care centers in the county was appropriate. The data collection procedures are similar for all subjects since a similar questionnaire with 29 questions was used in each PHCC that participated in the study. Consequently, this data collection instrument was reliable and valid to generate findings that could be representative of the entire population. Nonetheless, the researchers did not establish the reliability and validity of the data collection instruments prior to the study. The research does not also provide information on methods utilized by the researchers to test the reliability and validity of this data collection instrument. This is a major drawback of this study given that testing the reliability and validity of data collection instruments is crucial towards generating accurate findings. Data Analysis For data analysis, the researchers utilized statistical software STATA 9.0 in which summary and frequency tables was used to evaluate all variables in this research (Sundborg et al., 2012, p.3). The level of measurement was suitable for the statistics used since Pearson's chi-square test was used to determine statistical significance. The descriptive statistics reported in this study include nurses' perception of common attitudes toward IPV, patterns in confirming women's exposure to IPV, and preparedness of nurses of handle women exposed to IPV. The inferential statistics reported in this study are how nurses received training for dealing with IPV either vocational/professional training or personal initiative. These inferential statistics were suitable for the hypothesis since they indicated nurses' preparedness to handle patients exposed to IPV. However, the level of significance and reliability for the current study is not reported in the data analysis section despite the use of a two-step multivariate logistic regression analysis to test the hypothesis. Analysis of Findings/Discussion The hypothesis in this study was supported as the researchers found that there are weaknesses about nurses' preparedness to care for female patients exposed to intimate partner violence. The results of this study were interpreted in the context of the hypothesis, theoretical framework, and problem. This is evidenced in the fact that researchers examined the results based on personal attitudes of nurses, organizational conditions, personal experiences, and training. Following this contextual analysis, the study provides generalizations on the extent with which nurses are prepared to care for women exposed to IPV. There are two unwarranted interpretations of causality made by these researchers i.e. organizational conditions and personal attitudes towards intimate partner violence. The tables and graphs utilized in the data analysis section support the text or findings in the discussion section. Conclusions, Implications and Recommendations The study concluded that nurses are relatively unprepared to offer appropriate care to women exposed to IPV (Sundborg et al., 2012, p.10). These results are presented in a concise manner and supported by the literature. The researchers also identified limitations of the study including the wide nature of the confidence intervals in the regression models. Secondly, participants who did not return or answer the questionnaires were not further contacted. The study identified one implication for nursing practice i.e. using the study's findings to establish nursing educational programmes for practitioners in primary health care to help improve preparedness in caring for women exposed to IPV. However, the study does not provide recommendations for future research. Reference Sundborg, E.M., Saleh-Stattin, N., Wandell, P. & Tornkvist, L. (2012, January 10). Nurses' Preparedness to Care for Women Exposed to Intimate Partner Violence: A Quantitative Study in Primary Health Care. BMC Nursing, 11(1), 1-11. https://www.paperdue.com/customer/paper/data-analysis-and-nurses-2162714#:~:text=Logout-,DataAnalysisandNurses,-Length3pages Read the full article

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Stata Programming: Mastering Household Survey Data Processing

Programming an estimation command in Stata

David Drukker, StataCorp's Executive Director of Econometrics, wants to teach you how to write an estimation command in Stata. He wants your command to act and work just like official Stata estimation commands. He wants your command to support robust standard errors, to perform predictions, and to work with Stata's postestimation commands like test and margins. He wants to show you how easily you can accomplish all this and more.

David is writing a blog series to take you from a Stata programming novice to an accomplished Stata estimation command programmer. He wants you to produce commands you will be confident to share with colleagues, but he won't be disappointed if you just use them yourself.

You will learn how to

use macros effectively

program ado-files

process options

allow for if and in qualifiers

support time-series and factor-variable operators

program in Mata

validate and certify your estimator

and much more

Stata has many tools that simplify all aspects of programming estimation commands. David carefully leads you through all of these tools so you can understand why they exist and how you can leverage them to make hard things easy.

Read More.....

Household survey data is essential for informing policy, evaluating programs, and understanding social and economic dynamics. However, processing this data can be complex due to its size, structure, and variability. Stata, a statistical software widely used in academia and by professionals, provides robust tools for managing and analyzing such data. If you are dealing with household surveys like the Demographic and Health Surveys (DHS), Living Standards Measurement Study (LSMS), or national census data, mastering Stata will help you unlock valuable insights.

In this article, we’ll guide you through the essential steps to master household survey data processing using Stata. From setting up your workspace to generating descriptive statistics and running regressions, we’ll cover it all.

1. Introduction to Household Survey Data

Household surveys typically collect information on demographics, income, education, health, employment, and living conditions. These datasets are often large and complex, involving multiple files and variables that require careful management and analysis.

Types of Household Surveys

Cross-Sectional Surveys: These surveys provide a snapshot of households at one point in time.

Panel Surveys: These surveys track the same households over multiple periods, allowing for the analysis of changes over time.

2. Why Use Stata for Household Survey Data?

Stata is particularly suited for survey data due to its powerful data management, statistical analysis, and visualization tools. Here are a few key reasons:

Efficient Data Management: Stata can handle large datasets with ease, even those with millions of records.

Survey-Specific Commands: Stata has built-in functions for managing survey data, including handling complex survey designs (e.g., stratified, clustered samples).

Reproducibility: Stata allows you to write and execute do-files, ensuring that your work is reproducible and well-documented.

3. Setting Up Your Workspace

Before diving into data processing, it's essential to set up your Stata workspace correctly. This includes organizing your data, creating directories, and preparing log files to keep track of your work.

Organizing Your Files

Raw Data Files: Store the original data files in a designated folder.

Do-Files: This is where you’ll write your Stata code.

Output: Have a separate folder for storing output files, including tables, graphs, and log files.

4. Importing and Cleaning Data

Importing Data

You’ll often receive household survey data in formats like .csv, .dta, or even .sav (SPSS format).

Cleaning Data

Data cleaning is the most critical part of processing household survey data. It involves dealing with missing data, recoding variables, and creating new variables for analysis.

5. Merging and Appending Data Files

Household survey data often comes in multiple files, such as individual-level and household-level data. To perform a comprehensive analysis, you’ll need to merge these files.

Merging Data Files

You can merge datasets by using unique identifiers like household ID (hhid) and person ID (pid).

6. Understanding Survey Weights

Household surveys are often conducted using complex sampling techniques. This makes it crucial to apply sampling weights to get accurate, nationally representative estimates.

7. Generating Descriptive Statistics

Descriptive statistics provide an overview of your dataset and help you understand the distribution of key variables. Use Stata’s summarize and tabulate commands to generate basic statistics like means, frequencies, and standard deviations.

8. Data Visualization in Stata

Stata provides a variety of tools to create visual representations of your data, which can help you spot trends and outliers.

9. Regression Analysis

Once you’ve cleaned and explored your data, you can perform regression analysis to understand relationships between variables.

10. Exporting Results

After your analysis, you’ll likely need to export results for reports or presentations. Stata makes it easy to export tables and graphs.

Conclusion

Mastering household survey data processing in Stata takes time and practice, but the rewards are well worth it. Whether you're analyzing socio-economic trends or evaluating policy impacts, the ability to manage, clean, and analyze household data is an invaluable skill. By understanding key concepts such as data merging, applying survey weights, and conducting regression analysis, you can unlock powerful insights that drive meaningful change.

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Stata Programming-Mastering Household Survey Data Processing

In today’s data-driven world, processing and analyzing household survey data has become an essential skill for researchers, data scientists, and analysts. Among the various tools available, Stata programming stands out as one of the most powerful and versatile tools for managing and analyzing survey data. Whether you are involved in academic research, policy formulation, or project evaluations, mastering Stata Programming-Mastering Household Survey Data Processing can significantly boost your career and analytical capabilities. Let’s dive into how you can efficiently manage household survey data using Stata.

Why Stata for Household Survey Data?

Household surveys are incredibly complex, with multiple variables, hierarchical data structures, and large datasets. The challenge lies in managing this data effectively, cleaning it, and conducting insightful analysis. Stata programming simplifies this process with its easy-to-learn commands and powerful data management capabilities.

Whether you’re a beginner or someone with prior programming experience, Stata offers an intuitive interface combined with the flexibility of programming languages to handle survey data of all scales. Stata's functionalities, like data management, regression analysis, and hypothesis testing, make it an ideal choice for mastering the intricacies of household survey data.

Getting Started with Stata Programming

Before diving into household survey data processing, you need to familiarize yourself with the basics of Stata. Start with learning simple commands, such as:

Data entry and management – Input your data into Stata, whether manually or by importing from external databases like Excel or CSV files.

Data cleaning – Learn how to manage missing data, correct errors, and standardize your datasets using commands like replace, gen, and tabulate.

Descriptive statistics – Run basic descriptive statistics like mean, summarize, and tabulate to understand the structure and key trends in your survey data.

Once you're comfortable with the basics, you can move on to more advanced concepts like merging datasets, reshaping data, and conducting inferential analyses.

Household Survey Data: A Brief Overview

Household surveys are structured datasets designed to collect information on various aspects such as household income, demographics, education, and employment. These surveys help policymakers and researchers analyze trends and patterns in society. Some of the widely used household surveys include the Demographic and Health Survey (DHS), Living Standards Measurement Study (LSMS), and Multiple Indicator Cluster Surveys (MICS).

The primary goal of household surveys is to gather accurate and actionable data to inform policy decisions. However, the raw data from these surveys can be overwhelming, often containing thousands of observations and hundreds of variables.

This is where Stata programming becomes essential. Mastering Stata Programming-Mastering Household Survey Data Processing allows you to handle such data with ease, ensuring that your analysis is accurate, efficient, and insightful.

Key Steps in Household Survey Data Processing Using Stata

Data Importation and Preparation

The first step in handling household survey data is to import it into Stata. Stata supports various file formats such as .dta, .csv, and .xls.

After importing the data, you’ll need to clean it. This involves removing duplicates, dealing with missing values, and reformatting variables. Stata’s commands like drop, keep, and duplicates are highly effective in this process.

Data Cleaning and Transformation

Household survey datasets often contain missing or inconsistent data. Using Stata's programming tools, you can filter and clean your data systematically.

For example, you can use the egen command to create new variables that summarize existing data, or the recode command to change the format of a variable.

Handling Hierarchical Data

Household survey data often consists of multi-level data, where each household is represented by several individuals. Understanding how to manage this data hierarchy is crucial.

Stata allows you to group variables and conduct multi-level analyses. For example, you can use the reshape command to change data from a wide format to a long format (or vice versa) depending on your analysis needs.

Merging and Appending Datasets

Often, you may need to combine different datasets, such as merging household-level data with individual-level data. Stata's merge and append commands are invaluable for this process.

Ensure that the datasets share common identifiers to avoid errors during merging.

Analyzing Survey Data

Once your data is cleaned and organized, Stata’s programming tools allow you to perform in-depth statistical analysis, including regressions, correlation analyses, and time-series analysis.

You can use commands like regress, correlate, and anova to explore relationships and test hypotheses. Stata also has specific commands for survey data analysis, such as svyset and svy: mean.

Stata Programming for Policy and Social Research

For researchers working in policy or social sciences, Stata programming is a valuable asset. With large-scale household survey data, you can examine the social structure, understand economic trends, and identify patterns that can influence decision-making. Stata Programming-Mastering Household Survey Data Processing becomes particularly important when working on projects like poverty mapping, labor market studies, or health and education research.

Stata’s user-friendly syntax allows for quick and accurate results, while its graphical tools offer the opportunity to create publication-quality charts and graphs.

Popular Commands in Stata for Household Survey Data

Here are some of the trending and frequently used commands in Stata programming for survey data processing:

summarize – Generates summary statistics for the variables.

tabulate – Creates frequency tables for categorical variables.

xtset – Defines panel data settings, useful in household surveys.

merge – Combines multiple datasets.

reshape – Reshapes datasets from wide to long format or vice versa.

egen – Generates new variables using existing data.

Mastering these commands will help you become proficient in handling complex survey datasets.

Free AI Tools to Support Data Processing

As you master Stata Programming-Mastering Household Survey Data Processing, you’ll find that AI can also assist in automating some tasks. There are several free AI tools that can complement your work with Stata. Tools like ChatGPT can help generate code snippets, provide explanations for complex programming tasks, or even automate data cleaning to some extent.

By integrating AI-powered tools, you can speed up your household survey data processing and focus on generating insights. Free AI tools offer an opportunity to further simplify your workflows, making data management tasks more efficient. While these tools aren’t a replacement for Stata programming, they can certainly enhance your productivity.

Benefits of Mastering Household Survey Data Processing in Stata

Mastering Stata Programming-Mastering Household Survey Data Processing offers multiple benefits:

Increased Efficiency – With Stata, you can handle and process large datasets quickly, saving time and effort.

Advanced Statistical Analysis – Stata provides a wide array of statistical techniques, making it ideal for conducting complex analyses on household data.

Data Visualization – Stata’s graphing tools allow you to present data visually, which is key in research and policy-making.

Improved Accuracy – The precision offered by Stata reduces the risk of errors during data processing and analysis.

Career Growth – Proficiency in Stata programming is highly sought after in fields like economics, public health, and social sciences.

Conclusion

Mastering Stata Programming-Mastering Household Survey Data Processing is a powerful skill for anyone involved in data analysis. It opens doors to comprehensive and insightful analysis, allowing you to extract meaningful conclusions from vast household survey datasets. Whether you’re a researcher, a policy analyst, or someone looking to boost their data processing skills, Stata offers the tools you need.

By learning to navigate the complexities of household survey data with Stata programming, you’ll position yourself as a valuable asset in the data-driven world. And remember, while mastering Stata is crucial, incorporating tools like free AI can further enhance your workflow and streamline the entire data processing journey.

Start today, and see how Stata programming transforms the way you approach household survey data!

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SPSS Help for Social Science Students in Analyzing Survey Data

Data analysis is much needed skill to be acquired for any social science student especially for those in research and surveys. One of the most widely used programs for this purpose is SPSS (Statistical Package for the Social Sciences). SPSS is adopted in academies and professions for the reliability of the statistical functionalities and ease of use of the application. This post aims to spss help for students pursuing social science courses and are seeking guidance on the use of SPSS for data analysis. We will discuss the basics of SPSS, how spss has become an important tool for research in social sciences, common difficulties that student face in spss and some helpful solutions to overcome these difficulties.

What is SPSS?

SPSS is an acronym for ‘Statistical Package for the Social Sciences’. It is one of the most popular statistical analysis software, designed for handling quantitative data. The SPSS was developed by Norman H. Nie, C. Hadlai Hull, and Dale H. Bent in the 1960s as a statistical package for the social science disciplines. It has developed into one of the most important and versatile tools of data analysis for use by researchers, academicians, and professionals in areas such as psychology, sociology, political science, public health and marketing. SPSS provides robust statistical operations like descriptive stats, bivariate statistics, linear regression, multivariate regression and many other functions. It gives the capability to import, process, and analyze data, test hypothesis, and generate comprehensive reports with tables and graphs.

Importance of SPSS in Social Science Research

In social science research, studying people’s behavior, societal trends, and social phenomena may involve gathering and evaluating complex collection of data. This is where SPSS is most useful as it makes analysis and generating the results in no time so that the researcher can devote more time towards identifying the patterns and finding insights.

Why SPSS is Preferred in Social Sciences:

Ease of Use: SPSS is easy to use for beginners, as it has a simple graphical user interface especially designed for students and researchers having basic knowledge of statistics. Most of the operations can be performed through the use of menus and dialog boxes, thus minimal programming experience is required for its operation.

Versatility: SPSS can analyse diverse types and formats of data and therefore can be used in various social science research such as experimental research, survey analysis, and observational research.

Comprehensive Statistical Capabilities: SPSS offers almost all advanced statistical procedures that suits the diverse research needs in social sciences. This includes methods for dealing with handling complex survey data, which is common in social science research.

Support for Large Datasets: Social Science research involves big datasets with numerous variables. Due to the ability of SPSS to handle large data sets, it has become the researcher’s preferred data analysis tool.

Integration with Other Software: It can also import and export data using data files from other softwares such as Excel, SAS, Stata and many others, which is viable for researchers who use various tools in their research process.

Using SPSS for Analyzing Survey Data in Social Sciences

Conducting analysis on survey data is one of the common tasks in social sciences research. Surveys are usually conducted to gather information concerning the various areas of life interest, such as the public opinion, consumer behavior to psychological traits and social attitudes. Analyzing survey data with SPSS involves several key steps:

1. Data Import and Preparation: Before analyzing survey data in SPSS, the data is required to be imported into the software. Some of the file formats that can be used includes excel, csv and text files by SPSS. Once the dataset in the raw format is imported, it must be pre-processed before analysis. This involves performing data screening to identify missing values, recoding variables, and creating new variables as needed.

Example: Suppose a student is analyzing survey data on social media usage among college students. The first step would be to import the survey data into SPSS and then check for any missing values or outliers that could affect the analysis.

2. Descriptive Statistics: The next step is descriptive analysis which involves the use of statistical tools to describe the data. This encompasses estimating measures of central tendencies such as mean, median, mode and measures of dispersion such as standard deviation, variance and range. Descriptive statistics are used to understand the data set and to recognize the patterns which may exist.

Example: The student might calculate the average number of hours spent on social media per day by college students and the standard deviation to understand the variability in social media usage.

3. Inferential Statistics: Inferential statistics are used to derive inferences about a population based on a sample. This includes hypothesis testing, in which one is in a position to test theories and assumptions.

Example: If the student wants to test whether there is a significant difference in social media usage between male and female students, they could use a t-test or ANOVA in SPSS.

4. Regression Analysis: Regression analysis is one of the most powerful statistical techniques that is commonly used for studying the relationship between two or more variables. In social sciences, regression is usually applied to explain how various factors affect an outcome. 

Example: The student might use regression analysis to examine how factors like age, gender, and academic performance influence social media usage among college students.

5. Data Visualization: SPSS offers a range of tools for visualizing data, including histograms, bar charts, scatter plots, as well as pie charts. Visualizations are much crucial for communicating the results of an analysis much effectively.

Example: The student could create a bar chart to visually compare the average social media usage between different demographic groups.

6. Interpreting and Reporting Results: The last part of the analysis is the interpretation of the results, and expressing them in a simple and comprehensible language. This includes the presentation of the results to the research questions and the interpretation of the results in the light of the questions. 

Example: The student might interpret the results of their analysis to conclude that female students spend significantly more time on social media than male students and discuss the potential reasons and implications of this finding.

Challenges Faced by Social Science Students in Learning SPSS

SPSS is one of the most powerful tools, and learning to use it effectively can be a challenging work for many students, particularly to those who are new to the field of statistics or data analysis. Some of the common challenges includes:

Understanding the Software Interface: The structure of the SPSS interface is good and easy to use, but due to the availability of multiple sub-menus and steps, the first-time users may get confused.

Choosing the Right Statistical Test: A perennial problem that social science students encounter is the kind of statistical test to apply in a certain analysis because the right test determines the validity of results. 

Interpreting Output: The output generated through SPSS can be confusing, containing numerous tables and figures. Interpreting them and deriving meaningful conclusions might be challenging.

Data Preparation: Data cleaning, transformation and recoding may require careful approach which at times may become challenging.

Application of Results: Connecting the statistical findings to a theory can be challenging, especially for the young statisticians or the students.

SPSS Help for Students: Specific Questions and Research Studies in Social Science

Specific questions that students may expect in their exams include analysing survey data, performing correlation and regression analyses, conducting t-tests and ANOVA, and examining categorical data through chi-square tests. For instance, a student might need to explore the relationship between socioeconomic status and educational attainment, assess the impact of a new policy on public opinion, or evaluate psychological traits using survey responses.

Types of Research Studies Using SPSS

In the social sciences, SPSS is applied both in quantitative and qualitative research projects. Quantitative research include surveys and experiments in which SPSS assists in analysing numerical data to find out whether hypothesis is supported or not, and to find hidden trends and make predictions. SPSS can be used in qualitative analysis to analyse coded data such as open-ended responses in interviews which facilitates pattern recognition. Cross-sectional studies, longitudinal data analysis and experimental study designs are commonly carried out using SPSS in social sciences.

Tips and Tricks for Using SPSS in Social Sciences

Utilize Syntax Commands: SPSS has a point-and-click user interface. But also mastering the syntax commands will save time and make the work reproducible.

Data Cleaning and Preparation: It is crucial always to clean and prepare your data before any analysis can be carried out. It involves examining for cases of missing data, outliers as well as ensuring that the variables are correctly formatted.

Use Descriptive Statistics First: Begin with Descriptive statistics in case you want to have a look at your variables before diving into more complex analyses. This can help identify any anomalies or patterns.

Explore Graphical Options: SPSS help students in providing numerous graphical options for the process of data visualization. Use charts and graphs for better understanding of your data and to effectively communicate your findings.

Why Students should Opt for SPSS Help from Experts?

SPSS assignments are sometimes complicated since they involve core statistical knowledge and the software program. That is where SPSS help for Students can be immensely useful to you. We provide professional expertise to complete your assignments with precision and detail based on the specific requirements and rubric. Our USP lies in the personalized approach we adopt for every student, detailed explanations of the results and inclusion of examples that enable students not just to complete their assignments but to learn how to do them as well. Engaging with a SPSS analysis help expert can minimize errors, improves accuracy and analytical skills, improves grades.

Would you like to experience and avail SPSS help for assignments? Communicate with us for details on how our SPSS help service for students can support your academic journey.

Also Read: 7 Key Steps to Perform Structural Equation Modelling in SPSS Assignments

Helpful Resources and Textbooks for Learning SPSS 

For improving SPSS analytical skills, the following resources provides much needed spss help for students:

"Discovering Statistics Using IBM SPSS Statistics" by Andy Field

"SPSS Survival Manual" by Julie Pallant

IBM SPSS Help and Tutorials

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Unveiling My STATA Success Story: StatisticsHomeworkHelper.com's Game-Changing Support

As a student navigating the complex world of statistics, I've often found myself grappling with data sets, equations, and analyses that seem more like hieroglyphics than meaningful information. But amidst the confusion, there emerged a shining beacon of hope: statisticshomeworkhelper.com. Let me take you on a journey through my experience with this remarkable service and how they not only helped me conquer my statistics assignments but also empowered me to excel in a subject I once feared.

From the moment I stumbled upon statisticshomeworkhelper.com, I knew I had found the solution to my academic woes. With the daunting task looming over me to "do my statistical analysis homework using STATA," I turned to them with a mixture of skepticism and desperation. Little did I know that this decision would mark the beginning of a transformative journey in my statistical understanding.

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One of the most impressive aspects of statisticshomeworkhelper.com was their proficiency in STATA, a statistical software package widely used for data analysis. As someone who had previously struggled to navigate the complexities of this tool, witnessing their mastery was nothing short of inspiring. They effortlessly manipulated data, conducted regression analyses, and produced visually stunning graphs—all with the finesse of seasoned professionals.

But what truly set statisticshomeworkhelper.com apart was their personalized approach to learning. Instead of simply providing me with a finished assignment, they took the time to explain each step of the process, demystifying statistical concepts that had once seemed impenetrable. Through clear and concise explanations, they empowered me to not only understand the solution but also replicate it on my own—a skill that has proven invaluable in my academic journey.

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As I delved deeper into my statistics assignments with the support of statisticshomeworkhelper.com, I began to notice a profound shift in my confidence and understanding. What once felt like an insurmountable mountain of data now appeared as a series of manageable challenges, each waiting to be conquered. With each assignment completed, my proficiency in statistics grew, paving the way for newfound academic success.

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In conclusion, my experience with statisticshomeworkhelper.com has been nothing short of transformative. From helping me navigate the complexities of STATA to demystifying statistical concepts, their unwavering support has enabled me to excel in a subject I once feared. If you find yourself struggling with statistics assignments, I wholeheartedly recommend reaching out to statisticshomeworkhelper.com. Trust me, you won't be disappointed.

In the ever-evolving landscape of academia, statisticshomeworkhelper.com stands as a beacon of excellence—a testament to the power of knowledge and the transformative impact it can have on our lives. With their support, I have not only conquered my statistics assignments but also unlocked the true potential of my academic journey. So, if you ever find yourself faced with the daunting task of "do my statistical analysis homework using STATA," remember that statisticshomeworkhelper.com is only a click away, ready to guide you toward success.

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Excellent Stata Assignment Assistance By the Experts at MyAcademicHelps.com

One of the first statistical software programmes available is called Stata. Stata is an intuitive programme with a straightforward user interface written in C. Therefore, it makes sense that it is widely used in the academic setting and is a preference among students. However, knowledge gaps, complicated subjects, and challenges with problem-solving are the leading causes of Stata assignment issues.

The best professional Stata assignment help experts are available at Myacademichelps.com to provide outstanding Stata assignment help. SMEs with graduate and post-graduate degrees in statistical data, math, and computer science collaborate to produce outstanding Stata solutions.

What Does STATA Software Mean?

STATA is an all-inclusive collection of statistical tools. It offers all you need for deep learning, data management, and design. It is mainly used by economics, medical, and political science researchers to examine data trends. It offers commands and a graphical interface, making the application easier to perform.

Any source of information can be retrieved using the STATA application. One can access the same files by duplicating a file without making any modifications to the original. A user can choose any document and drag any information to the main page without opening it by interacting with the file storage.

Stata's benefits:

Both novice and experienced users can perform analysis using drop menus or syntax.

For modelling structural equations, there is an excellent built-in assistance function. Models can be defined using a path diagram or syntax.

A sizable and active online community exists for Stata. You can ask the locals for assistance with cutting-edge statistical techniques.

Multitasking is supported by Stata software because multiple do-files can be open at once. This has the significant benefit of making it simpler to use the copy/paste feature from many other projects' do-files.

Stata does repetitive analysis quite well when loops and macros are utilised in a do-file.

Stata's creators deliver software updates with new components and bug fixes every two months.

The fact that it is politely priced and free of added expenditures is an added blessing.

Because it is simple to use and quite powerful, Stata is a programme many people enjoy.

Many students and professionals who use Stata for administrative work may find it challenging to use Stata for projects. We offer online assistance that delivers guidance on addressing your Stata assignment and aid with Stata appointments to aid inhabitants who may have problems using Stata.

Why Do You Need Online Help with Stata Assignments?

Many people may find it challenging to utilise Stata for assignments and projects because they are either unsure what to do or because doing so necessitates a high level of computer expertise, which many learners require.

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Source: https://businesslawassignments.wordpress.com/2022/07/07/excellent-stata-assignment-assistance-by-the-experts-at-myacademichelps-com/

[automaticworktimereports]

Quill - Narrative Science

Ets Research: Automated Scoring Of Writing Quality

Table of ContentsAssociated Press - Automated InsightsAutomated Reporting Software & Tools: Report Automation ToolAutomated Journalism - WikipediaAutomated Report Generation With Papermill: Part 1 - Practical ...Automated Generation Of Clinical Study Reports Using Sas ...

As marketers in 2020, there's one significant thing that we share: We're driven by data. No matter whether we're copywriters, social media managers, videographers, or web designers, information is crucial to assisting us figure out which jobs are effective, which methods might require more of a budget plan, and which methods we need to leave behind.

Even if you have an analytics software that tracks a project's traffic, engagements, ROI, and other KPIs, you'll likely still require to take some time to arrange these numbers, evaluate them, and develop an understandable way to report on your tasks to your group or clients. In the past, marketing companies and companies entrusted full-timers with reporting-related duties. automate dashboard.

Best Reporting Tools & Software Of 2021 ...thedigitalprojectmanager.com

This is an issue that my Cleveland-based marketing firm, PR 20/20, ran into a few years back. As part of our process, we develop monthly efficiency reports for each of our customers. When we produce them, we pull the data from HubSpot and Google Analytics. Then, we compose a report to describe the data to our colleagues, customers, and project stakeholders.

However, although they were assisting our clients, creating them was holding our group back. While our clients found the reports valuable, the process of pulling the data, examining it, and drafting the reports easily took 5 hours per client, monthly. This took our online marketers away from jobs that could have been productive in the long run, such as brainstorming originalities and strategies that could noticeably assist their customers.

Automated Journalism – Ai Applications At New York Times ...

Whenever you're trying to try out or implement a new strategy, you'll desire to investigate the subject thoroughly. For example, you'll wish to recognize your spending plan and after that check out software that fits into it. You'll also desire to identify the pros and cons of any software application you consider. This will help you much better familiarize yourself with the world of AI and which tools can actually assist you.

Prior to deciding that we wished to streamline our reporting technique, we 'd been researching AI through resources at our Marketing AI Institute. The Institute is a media company that intends to make AI more approachable for marketers. real-time progress reporting. Given that we released the business, we've released more than 400 posts on AI in marketing.

2 billion. After learning more about how AI had already streamlined lots of marketing-related procedures, we decided to explore how automation and artificial intelligence could assist us with our clients at PR 20/20. We ended up being obsessed with how smarter technology could increase revenue and reduce costs. At the same time, we found natural language generation (NLG) technology that wrote plain English automatically.

You have actually experienced NLG anytime you've utilized Gmail's Smart Compose feature. Or, when you hear Amazon's Alexa react to your voice questions. Once we discovered a possibly useful NLG software, we chose to run an experiment to see if the AI technology could partially or totally automate our efficiency report composing process.

'Automated Writing': Implications For Digital Communicators ...

Now, the next step is to look for software application that works for your service. Here are a couple of things you'll need to think about: You'll want to consider the cost of any of the software application's memberships or charges, in addition to the expense to implement it. For example, you might need to contract or hire an engineer to prepare your information and take any steps to ensure the software application works smoothly.

Be sure to comprehend what you'll need to do if something isn't working correctly so you do not incur any emergency expenses. As an online marketer, you will not wish to depend on a full-time engineer to use AI software application to run your reports. You'll wish to purchase software application that your less tech-savvy staff member can eventually get trained on and discover. automated reporting dashboards.

As you choose software, you'll also desire to track down case research studies, reviews, or user testimonials that explain how a business utilized the software to run reports or finish a similar activity. This will provide you a concept of if the item you're thinking about has a good track record or credibility in the AI software application market.

Here are two highly-regarded examples: Domo is a data visualization and reporting tool that integrates with major information and analytics platforms consisting of Google Analytics. When you link these platforms, you can utilize a dashboard to set up and generate information visualizations or reports for your clients. These visualizations include pie charts, other graphs, and word clouds.

Vphrase - Get Insights From Your Data In Natural Language

The platform provides guides on how to develop datasets or spreadsheets that its algorithms will acknowledge as well as a drag and drop guide which asks you to publish specific details such as "Regular monthly Spending plan." Here's a quick demo that shows Domo in action: This reporting software permits you to produce reports or reporting dashboards that your group and customers can edit and cross-collaborate on.

reporting tools ...opensource.com

Aside from data visualizations, you can likewise add boxes to your dashboards that show you scorecards that note whether you're striking your goals or not, in addition to filters that help you drill down on specific elements of your project. Here's a demonstration discussing how small businesses such as nonprofits can take advantage of the software application's control panel reporting features: No matter which product you choose, you'll likely require to prepare your information in a way that your software's robot or algorithm could easily recognize and evaluate - automatic report.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

The software application needed structured information in columns and rows to generate text. So, initially, we needed to pull HubSpot and Google Analytics information into spreadsheets. Due to the fact that doing this manually would take too much time and limit the prospective time saved with automation, we utilized APIs and constructed our own algorithm utilizing Google Apps Scripts to pull data into a Google Sheet.

We knew NLG software would be unlikely to deal with completely customized reports well. So, we developed a design template for these reports that didn't change each month. To develop a format for each report, we identified a set of 12 typical questions we were trying to respond to for clients each month: How much traffic concerned your site, and how does that compare to the previous month? In 2015? How engaged was last month's website traffic? What were the top traffic-driving channels? Was there fluctuation in general traffic, and if so, what caused it? How did the blog carry out last month? How engaged was blog traffic? What were the top-performing post? Existed any modifications in blog site traffic last month, and if so, what caused them? The number of goals or new contacts were generated last month? What were the leading transforming pages? Where did objectives or new contacts come from? Was there any change in overall objectives or lead volume, and if so, what was accountable? A good AI software application will either allow you to produce files or even dashboards, as your reports.

Automated Writing Evaluation - Excelsior College Owl

As soon as we 'd structured our information and established a standard report format, we needed to translate our standard report format into an NLG design template. The design template was basically a completed variation of a performance report. When the NLG software runs, this report gets copied into the NLG software. Then guidelines are applied to the copy to programmatically upgrade what's written based on the structured information offered.

------------[ 1 ]------------

Automated Reports - Jotform

Table of ContentsHow Report Automation Can Improve Your Reporting Process ...Automated Content: Can Algorithms Write Your Content For You?Automated Reports And Dashboards In R - Nandeshwar.infoSitekick - Automated Client ReportsReproducible And Automated Reporting Using Stata

The final output could be a CSV, Word, or Google Doc file. Even if you're dealing with a credible AI software application, you'll still wish to evaluate it and troubleshoot any concerns that emerge. This prevents any AI-related occurrences from happening when the tool is actively being utilized by workers or on tight due dates.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

And we eventually perfected the process to regularly produce clear, accurate automatic performance reports. If a software service provider that you work with offers a trial or discount for evaluating out their item, leverage it. This will permit you to witness first-hand if the cost of the product exceeds its benefits, or provide you time to recognize if there is a better product that you ought to be using - automatic dashboard.

When you do this, here are a few things that you'll desire to examine: The quantity of time that the software is conserving employees, or if there were any bugs, just how much time the software cost. The amount of other efficient or revenue-generating tasks your team had the ability to get made with the extra time you had.

Regulatory Tracking & Compliance ...bulalaw.com

As we tracked our brand-new automated efficiency reports, we found that our tools took a portion of the time to produce the exact same report that we took hours to produce. Furthermore, the level of detail in our client reports is now constant throughout all accounts. Prior to we implemented AI tools, the reports were just as strong as the account team's comfort level of evaluating marketing performance reports.

Associated Press - Automated Insights

The only handbook part of the procedure now involves spot-checking the data for accuracy, applying some styling, and then sending. time reports. What when took us five hours per report now takes 10 minutes. While the initial process required to be handled by numerous teammates, just one employee is needed for spot-checking.

Although our group has the ability to gain access to AI providers and professionals for our in-office experiments, other small company online marketers can likewise take benefit of this technique rather economically. Nevertheless, bear in mind that AI execution can take some time. For us, we needed to put time into building structured datasets, in addition to our Report template so that our AI software application could read our analytics and draft reports appropriately.

Total information, faster conclusions, and much better decision-making digital-era success hinges on them (real-time progress reporting). But a company with a single variation of the truth, spreadsheets filled with accurate data, is still a few rungs brief of success. One reason: management requires easy-to-digest reports that interpret the numbers. That tends to lead to cleaner analyses and crisper decision-making.

These products drill-down into ab company's database and auto-produce easy-to-understand, written reports from the same data that Microsoft Excel uses to produce graphics. A few of these fairly new AI tools also known as natural language generation, or NLG, software are variations of the same innovation that assists significant media companies produce computer-written news items.

Automated Reporting With R Markdown

Anna Schena, a senior product manager at Story Science, another AI-generated writing toolmaker, says that "data storytelling" implies users don't have to learn how to evaluate spreadsheets or glean insights from long rows of dashboard dials. "Easy-to-understand language and one-click collaboration functions make sure that everybody in a business in fact comprehends the data, all the time," Schena states.

States Sharon Daniels, CEO of Arria: "NLG-driven, multi-dimensional stories are the development that [data-generated] visuals were years earlier. The big information issue was partly addressed with the advancement of service intelligence dashboards," she discusses. "But while visuals paint an image, they're not the total picture." Includes Daniels: "The ability to gain access to essential details in near real-time interacted as if composed by the business's leading expert, without predisposition, at an NLG writing-speed is truly astonishing - automated report writing." Deep inside analytics departments, NLG tools are getting traction.

Heitzman utilized AI-generated writing software application from Arria NLG to punch-up reports containing the graphics rendered by his propriety service intelligence (BI) software application. "We've developed narratives on enormous amounts of data to be able to immediately and clearly articulate the marketing worth we're giving our clients," Heitzman states. "The [Arria NLG] platform has actually dramatically reduced the amount of time and effort to discover insights." Brian O'Connor, lead director, advanced analytics international service services at biopharmaceutical giant AstraZeneca, boosted the graphics produced by Microsoft's Power BI.

Meanwhile, chip goliath Nvidia is enhancing its Tableau control panel with Automated Insights: "Automated Insights' Wordsmith has actually entirely changed how our group interacts with Tableau," says LaSandra Brill, head of digital planning and insights at Nvidia. "We can now ask the most essential questions straight within Tableau and receive real-time analysis from Wordsmith." IT options service provider Macrocomm includes story to its analytics program's output also: "By adding narratives to Eureka, we can produce summary findings in several languages that can be shared with stakeholders at a speed and scale not formerly possible," says Vinny Perumal, a handling director in the compnay's energies department.

Implementing Automated Reporting Solutions – What To ...

[howtocreatekpireport]

Automated Reporting: Liberate You From Repetition Work

Robot-writing Increased Ap's Earnings Stories By Tenfold ...

Table of ContentsReproducible And Automated Reporting Using StataReuters Uses Ai To Prototype First Ever Automated Video ...What Is Automated Storytelling? A Definition From Whatis.comAutomated Reports – Dr. Sonia CooperWritetolearn - A Web-based Ai-automated Writing Scoring ...

As online marketers in 2020, there's one major thing that we share: We're driven by information. No matter whether we're copywriters, social networks supervisors, videographers, or web designers, information is key to helping us figure out which projects achieve success, which strategies may need more of a spending plan, and which tactics we need to leave behind.

Even if you have an analytics software that tracks a campaign's traffic, engagements, ROI, and other KPIs, you'll likely still need to take time to organize these numbers, examine them, and come up with a reasonable method to report on your projects to your team or customers. In the past, marketing firms and agencies tasked full-timers with reporting-related responsibilities. automatic dashboard.

How report automation can improve your ...dashthis.com

This is an issue that my Cleveland-based marketing company, PR 20/20, faced a few years back. As part of our process, we develop month-to-month efficiency reports for each of our customers. When we create them, we pull the data from HubSpot and Google Analytics. Then, we compose a report to explain the data to our associates, customers, and job stakeholders.

However, although they were assisting our clients, creating them was holding our group back. While our customers found the reports valuable, the procedure of pulling the information, analyzing it, and drafting the reports easily took five hours per client, monthly. This took our online marketers far from jobs that might have been efficient in the long run, such as conceptualizing originalities and techniques that might significantly assist their clients.

Automatic Reporting Tools - Blog - Whatagraph

Whenever you're attempting to try out or implement a brand-new strategy, you'll want to investigate the topic completely. For example, you'll wish to acknowledge your spending plan and after that check out software application that fits into it. You'll also wish to figure out the pros and cons of any software you consider. This will assist you better acquaint yourself with the world of AI and which tools can really assist you.

Prior to choosing that we wished to streamline our reporting method, we 'd been looking into AI through resources at our Marketing AI Institute. The Institute is a media business that aims to make AI more approachable for marketers. how to create kpi report. Because we launched the company, we have actually released more than 400 posts on AI in marketing.

2 billion. After discovering how AI had currently structured lots of marketing-related processes, we chose to explore how automation and expert system could help us with our customers at PR 20/20. We ended up being consumed with how smarter technology might increase earnings and lower costs. At the same time, we discovered natural language generation (NLG) innovation that wrote plain English automatically.

You've come across NLG anytime you have actually used Gmail's Smart Compose function. Or, when you hear Amazon's Alexa respond to your voice queries. As soon as we discovered a potentially helpful NLG software, we chose to run an experiment to see if the AI technology could partly or completely automate our performance report writing process.

Quickly Generate Custom Branded Reports - Dradis Pro

Now, the next step is to look for software application that works for your organization. Here are a few things you'll need to consider: You'll wish to consider the expense of any of the software application's memberships or costs, in addition to the cost to execute it. For instance, you might require to agreement or work with an engineer to prepare your data and take any actions to make sure the software application works efficiently.

Make certain to understand what you'll require to do if something isn't working effectively so you do not sustain any emergency situation costs. As an online marketer, you will not want to depend on a full-time engineer to use AI software to run your reports. You'll wish to purchase software that your less tech-savvy group members can eventually get trained on and learn. automate dashboard.

As you choose software, you'll also want to locate case studies, evaluations, or user reviews that describe how a company utilized the software to run reports or complete a similar activity. This will provide you a concept of if the product you're thinking about has an excellent track record or reliability in the AI software application industry.

Here are 2 highly-regarded examples: Domo is an information visualization and reporting tool that integrates with major information and analytics platforms including Google Analytics. Once you link these platforms, you can utilize a control panel to establish and generate data visualizations or reports for your clients. These visualizations include pie charts, other graphs, and word clouds.

Creating An Automated Report In Word - Principal Toolbox 9.5

The platform uses guides on how to produce datasets or spreadsheets that its algorithms will acknowledge as well as a drag and drop guide which asks you to upload particular info such as "Regular monthly Budget plan." Here's a fast demonstration that shows Domo in action: This reporting software allows you to generate reports or reporting control panels that your group and customers can edit and cross-collaborate on.

Past Webinars Arria NLGarria.com

Aside from data visualizations, you can likewise include boxes to your dashboards that show you scorecards that keep in mind whether you're hitting your objectives or not, as well as filters that help you drill down on specific elements of your project. Here's a demonstration explaining how small companies such as nonprofits can benefit from the software's control panel reporting features: Regardless of which product you pick, you'll likely require to prepare your data in a manner that your software's robot or algorithm might quickly recognize and evaluate - real-time progress reporting.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

The software required structured information in columns and rows to produce text. So, first, we needed to pull HubSpot and Google Analytics information into spreadsheets. Because doing this manually would take excessive time and limit the possible time conserved with automation, we used APIs and constructed our own algorithm using Google Apps Scripts to pull information into a Google Sheet.

We knew NLG software application would be not likely to deal with totally custom-made reports well. So, we produced a template for these reports that didn't change every month. To create a format for each report, we identified a set of 12 typical concerns we were trying to respond to for clients each month: Just how much traffic concerned your website, and how does that compare to the previous month? In 2015? How engaged was last month's site traffic? What were the leading traffic-driving channels? Was there variation in general traffic, and if so, what triggered it? How did the blog perform last month? How engaged was blog traffic? What were the top-performing blog site posts? Were there any modifications in blog site traffic last month, and if so, what caused them? How numerous goals or new contacts were generated last month? What were the leading transforming pages? Where did goals or brand-new contacts originate? Was there any modification in total objectives or lead volume, and if so, what was accountable? A great AI software will either allow you to produce documents and even control panels, as your reports.

Implementing Automated Reporting Solutions – What To ...

When we 'd structured our information and established a basic report format, we needed to equate our standard report format into an NLG template. The design template was basically a completed variation of an efficiency report. When the NLG software application runs, this report gets copied into the NLG software. Then rules are applied to the copy to programmatically upgrade what's composed based on the structured information supplied.

------------[ 1 ]------------

Automate Email With Python. Using Python To Automate The ...

Table of ContentsRubrik As Built Report For Easier, Automated DocumentationGuide To Automated Journalism - Academic CommonsHow To Automate 70% Of Your Management Reporting ...5 Ways To Simplify Your Automated Test Cases - TechbeaconAutomated Reporting Systems & Tools To Boost Your Business

The last output might be a CSV, Word, or Google Doc file. Even if you're dealing with a credible AI software application, you'll still desire to test it and troubleshoot any concerns that emerge. This avoids any AI-related events from taking place when the tool is actively being used by employees or on tight deadlines.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

And we ultimately refined the procedure to regularly produce clear, accurate automated efficiency reports. If a software company that you deal with deals a trial or discount rate for testing out their item, take advantage of it. This will enable you to witness first-hand if the cost of the product surpasses its advantages, or offer you time to determine if there is a more suitable item that you should be utilizing - automate dashboard.

When you do this, here are a few things that you'll want to examine: The quantity of time that the software application is saving workers, or if there were any bugs, just how much time the software cost. The quantity of other efficient or revenue-generating jobs your team was able to get finished with the additional time you had.

Write an Effective Test Summary Report ...softwaretestinghelp.com

As we tracked our new automated performance reports, we found that our tools took a fraction of the time to produce the same report that we took hours to produce. Furthermore, the level of information in our customer reports is now consistent across all accounts. Before we implemented AI tools, the reports were only as strong as the account team's convenience level of examining marketing performance reports.

Automated Reporting Systems & Tools To Boost Your Business

The only handbook part of the procedure now involves spot-checking the information for accuracy, using some styling, and then sending. automatic reports. What as soon as took us five hours per report now takes 10 minutes. While the original procedure needed to be managed by multiple colleagues, just one employee is required for spot-checking.

Although our team is able to access AI providers and professionals for our in-office experiments, other small company online marketers can likewise benefit from this strategy somewhat economically. However, bear in mind that AI execution can take some time. For us, we needed to put time into building structured datasets, in addition to our Report template so that our AI software application could read our analytics and draft reports appropriately.

Complete details, faster conclusions, and much better decision-making digital-era success depends upon them (automatic report). However an organization with a single version of the fact, spreadsheets filled with precise information, is still a couple of rungs brief of success. One factor: management needs easy-to-digest reports that interpret the numbers. That tends to lead to cleaner analyses and crisper decision-making.

These items drill-down into ab organization's database and auto-produce easy-to-understand, written reports from the very same information that Microsoft Excel uses to generate graphics. A few of these reasonably new AI tools likewise called natural language generation, or NLG, software application are variations of the same innovation that helps significant media companies produce computer-written news items.

Automated Journalism – Ai Applications At New York Times ...

Anna Schena, a senior item manager at Narrative Science, another AI-generated composing toolmaker, says that "data storytelling" suggests users don't have to discover how to examine spreadsheets or glean insights from long rows of control panel dials. "Easy-to-understand language and one-click partnership functions guarantee that everyone in a company in fact understands the data, all the time," Schena states.

States Sharon Daniels, CEO of Arria: "NLG-driven, multi-dimensional stories are the breakthrough that [data-generated] visuals were years back. The huge information issue was partially addressed with the development of business intelligence control panels," she describes. "But while visuals paint a picture, they're not the complete photo." Includes Daniels: "The ability to gain access to crucial

[automaticreports]

Generate A Report: New In Mathematica 10 - Wolfram

This News-writing Bot Is Now Free For Everyone - Wired

Table of ContentsCreate Real-time Reports Automatically - PlectoAp's 'Robot Journalists' Are Writing Their Own Stories Now - The ...Create Real-time Reports Automatically - PlectoHow Report Automation Can Improve Your Reporting Process ...Vphrase - Get Insights From Your Data In Natural Language

As online marketers in 2020, there's one major thing that we have in typical: We're driven by information. Despite whether we're copywriters, social networks supervisors, videographers, or web designers, information is essential to assisting us determine which jobs are successful, which techniques may need more of a budget, and which tactics we require to leave behind.

Even if you have an analytics software that tracks a campaign's traffic, engagements, ROI, and other KPIs, you'll likely still need to take time to organize these numbers, examine them, and develop an understandable method to report on your tasks to your group or clients. In the past, marketing companies and firms entrusted full-timers with reporting-related duties. automatic reporting.

Automated Reporting – The Startup – Mediummedium.com

This is a problem that my Cleveland-based marketing firm, PR 20/20, encountered a few years ago. As part of our process, we create month-to-month efficiency reports for each of our clients. When we develop them, we pull the data from HubSpot and Google Analytics. Then, we compose a report to describe the data to our associates, customers, and project stakeholders.

However, although they were helping our clients, developing them was holding our group back. While our clients found the reports valuable, the process of pulling the information, evaluating it, and drafting the reports easily took 5 hours per client, monthly. This took our marketers away from jobs that might have been productive in the long run, such as conceptualizing originalities and techniques that might visibly help their customers.

Create Real-time Reports Automatically - Plecto

Whenever you're trying to explore or implement a new method, you'll want to research the topic thoroughly. For instance, you'll desire to recognize your budget plan and then look into software that fits into it. You'll also wish to figure out the benefits and drawbacks of any software application you think about. This will assist you much better familiarize yourself with the world of AI and which tools can really assist you.

Prior to deciding that we wanted to simplify our reporting technique, we 'd been researching AI through resources at our Marketing AI Institute. The Institute is a media business that intends to make AI more approachable for online marketers. real time reports. Considering that we released the business, we have actually published more than 400 short articles on AI in marketing.

2 billion. After discovering how AI had already structured dozens of marketing-related procedures, we chose to explore how automation and expert system might assist us with our customers at PR 20/20. We ended up being obsessed with how smarter innovation might increase income and reduce costs. At the same time, we found natural language generation (NLG) innovation that wrote plain English automatically.

You've encountered NLG anytime you've used Gmail's Smart Compose function. Or, when you hear Amazon's Alexa respond to your voice queries. As soon as we found a possibly practical NLG software application, we decided to run an experiment to see if the AI innovation might partially or totally automate our efficiency report writing process.

How Ai Tools Dropped One Agency's Reporting Time By 97%

Now, the next step is to browse for software application that works for your service. Here are a few things you'll need to consider: You'll want to consider the cost of any of the software application's memberships or costs, as well as the cost to implement it. For example, you might require to agreement or hire an engineer to prepare your information and take any actions to make sure the software works smoothly.

Make sure to comprehend what you'll need to do if something isn't working properly so you don't incur any emergency situation expenses. As an online marketer, you will not desire to count on a full-time engineer to utilize AI software application to run your reports. You'll wish to shop for software that your less tech-savvy employee can eventually get trained on and learn. automatic report.

As you pick out software application, you'll likewise want to find case research studies, reviews, or user reviews that explain how a company used the software to run reports or finish a comparable activity. This will give you an idea of if the product you're thinking about has a good performance history or trustworthiness in the AI software application market.

Here are two highly-regarded examples: Domo is a data visualization and reporting tool that incorporates with major data and analytics platforms consisting of Google Analytics. Once you link these platforms, you can utilize a control panel to establish and generate information visualizations or reports for your clients. These visualizations consist of pie charts, other charts, and word clouds.

Guide To Automated Journalism - Academic Commons

The platform uses guides on how to create datasets or spreadsheets that its algorithms will acknowledge as well as a drag and drop guide which asks you to submit specific information such as "Regular monthly Spending plan." Here's a quick demo that reveals Domo in action: This reporting software enables you to produce reports or reporting control panels that your group and clients can edit and cross-collaborate on.

Top use cases in automated report writingphrazor.ai

Aside from data visualizations, you can also add boxes to your dashboards that show you scorecards that note whether you're hitting your objectives or not, along with filters that assist you drill down on particular aspects of your job. Here's a demo describing how small companies such as nonprofits can take advantage of the software application's dashboard reporting features: Despite which item you select, you'll likely need to prepare your data in a way that your software application's robot or algorithm might quickly recognize and evaluate - time reports.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

The software required structured information in columns and rows to generate text. So, first, we needed to pull HubSpot and Google Analytics data into spreadsheets. Due to the fact that doing this manually would take too much time and restrict the possible time saved with automation, we utilized APIs and built our own algorithm utilizing Google Apps Scripts to pull data into a Google Sheet.

We understood NLG software would be not likely to handle totally custom reports well. So, we created a template for these reports that didn't alter each month. To produce a format for each report, we identified a set of 12 common questions we were attempting to address for clients monthly: Just how much traffic concerned your website, and how does that compare to the previous month? In 2015? How engaged was last month's site traffic? What were the leading traffic-driving channels? Existed change in general traffic, and if so, what triggered it? How did the blog carry out last month? How engaged was blog traffic? What were the top-performing article? Existed any modifications in blog traffic last month, and if so, what triggered them? The number of objectives or new contacts were produced last month? What were the leading converting pages? Where did goals or brand-new contacts originate? Existed any change in total goals or lead volume, and if so, what was accountable? An excellent AI software application will either allow you to develop files or even control panels, as your reports.

Ai-generated Reports Are The Write Stuff - Articles - Chief ...

When we 'd structured our information and established a basic report format, we needed to translate our basic report format into an NLG template. The design template was basically a finished version of an efficiency report. When the NLG software application runs, this report gets copied into the NLG software. Then guidelines are used to the copy to programmatically update what's written based upon the structured data supplied.

------------[ 1 ]------------

Automated Reports – Dr. Sonia Cooper

Table of ContentsReproducible And Automated Reporting Using StataQuickly Generate Custom Branded Reports - Dradis ProImplementing Automated Reporting Solutions – What To ...Automated Sports Journalism. The Anafut Case Study, The Bot ...Ax Semantics - Ai-powered Nlg Content Writing Software

The last output could be a CSV, Word, or Google Doc file. Even if you're dealing with a reputable AI software application, you'll still wish to evaluate it and repair any problems that come to light. This prevents any AI-related events from occurring when the tool is actively being utilized by employees or on tight due dates.

Plecto ApS

Address: Viby Ringvej 11, 1 tv

Phone: +45 71 99 71 60

Email: support@plecto.com

Real-time insights

And we ultimately perfected the procedure to consistently produce clear, accurate automatic efficiency reports. If a software application company that you deal with offers a trial or discount rate for evaluating out their item, take advantage of it. This will allow you to witness first-hand if the cost of the item exceeds its benefits, or give you time to recognize if there is a preferable product that you need to be utilizing - real time reports.

When you do this, here are a few things that you'll wish to examine: The amount of time that the software application is conserving workers, or if there were any bugs, how much time the software expense. The quantity of other efficient or revenue-generating jobs your team was able to get finished with the additional time you had.

How To Write Data Reports For Your ...datapine.com

As we tracked our brand-new automated performance reports, we found that our tools took a portion of the time to produce the exact same report that we took hours to create. Additionally, the level of information in our client reports is now consistent across all accounts. Before we executed AI tools, the reports were just as strong as the account team's comfort level of examining marketing efficiency reports.

Automated Reports And Dashboards In R - Nandeshwar.info

The only manual part of the process now includes spot-checking the data for precision, applying some styling, and then sending out. automate dashboard. What once took us five hours per report now takes 10 minutes. While the original procedure needed to be managed by multiple teammates, only one staff member is required for spot-checking.

Although our team is able to gain access to AI providers and professionals for our in-office experiments, other little business marketers can likewise make the most of this technique rather cost effectively. Nevertheless, keep in mind that AI application can take some time. For us, we needed to put time into building structured datasets, as well as our Report design template so that our AI software application could read our analytics and draft reports correctly.

Total details, faster conclusions, and much better decision-making digital-era success depends upon them (automatic reports). However an organization with a single variation of the fact, spreadsheets filled with precise data, is still a couple of rungs except success. One reason: management requires easy-to-digest reports that interpret the numbers. That tends to lead to cleaner interpretations and crisper decision-making.

These products drill-down into ab organization's database and auto-produce easy-to-understand, written reports from the exact same information that Microsoft Excel utilizes to generate graphics. A few of these reasonably new AI tools likewise referred to as natural language generation, or NLG, software are variations of the same technology that assists major media companies produce computer-written news items.

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Anna Schena, a senior item supervisor at Story Science, another AI-generated composing toolmaker, states that "data storytelling" implies users do not need to find out how to evaluate spreadsheets or obtain insights from long rows of dashboard dials. "Easy-to-understand language and one-click collaboration functions make sure that everybody in a company in fact comprehends the data, all the time," Schena states.

Says Sharon Daniels, CEO of Arria: "NLG-driven, multi-dimensional stories are the development that [data-generated] visuals were years back. The big information problem was partially resolved with the evolution of service intelligence dashboards," she describes. "However while visuals paint a photo, they're not the total photo."

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NEIGRIHMS Recruitment 2023: Research Officer, Project Technical, Project Assistant, Nurse & DEO Vacancy

NEIGRIHMS Recruitment 2023: North Eastern Indira Gandhi Regional Institute of Health & Medical Sciences, Shillong released an employment notification for the recruitment of various posts on a contractual basis for one year under the ICMR project "A Community-Based Study on Health-Related Quality of Life (HRQOL), Functional Status and Morbidity Profile among Elderly Persons Living in Rural Setting of Meghalaya". The last date for submission of the application will be April 20, 2023. 1. Post Name:- Research Officer- Scientist-B (Medical) - No of posts:- 1 (One) - Upper age limit:- 40 years. - Salary:- Rs. 61000/- per month - Essential Qualification:- Bachelor's degree (MBBS/BDS/AYUSH) from a recognized institute with one year of experience OR Postgraduate degree in Community Medicine/ Geriatrics/ Psychiatry from a recognized institute. - Desirable:- # Research/ Clinical experience in Geriatrics/ Psychiatry # Ability to handle SPSS/STATA or other statistical software(s). # Experience in handling ICMR-funded ad-hoc projects/ any other extramural project. 2. Post Name:- Project Technical Officer (Psychologist) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 32,000/- per month - Essential Qualification:– Bachelor’s degree in Psychology from a recognized institute with one year of work experience OR Master’s degree in Psychology from a recognized institute. - Desirable:- # Ph.D. in psychology # Experience in clinical assessment and use of various scales for neuropsychological assessment. # Experience in working at the community level. 3. Post Name:- Project Invest Assistant (Field Investigator) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 31000/- per month - Essential Qualification:- Graduate in Science/ relevant subject from a recognized institute with one year of work experience OR Master’s degree in the relevant subject from a recognized institute. - Desirable:- Experience in working at the community level and should be able to collect the relevant data. 4. Post Name:- Junior Nurse - No of posts:- 1 (One) - Upper age limit:- 32 years. - Salary:- Rs. 18000/- per month - Essential Qualification:- Graduate in Nursing (B.Sc Nursing) from a recognized institute with one year of work experience OR Master’s degree in Nursing from a recognized institute - Desirable:- Ability to handle Microsoft Office (Word, Excel, and PowerPoint). 5. Post Name:- Data Entry Operator (Gr. C) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 31000/- per month - Essential Qualification:- Intermediate OR 12 pass in Science stream from a recognized board or two years experience in Electronic Data Processing (EDP) work in any recognized organization. - Desirable:- Ability to handle Microsoft Office (Word, Excel, and PowerPoint). How to apply for NEIGRIHMS Recruitment 2023: Research Officer, Project Technical, Project Assistant, Nurse & DEO Vacancy? Interested and eligible candidates may submit their applications online through Google with the necessary information. The last date for submission of the application is 20th April 2023. Shortlisted candidates will be intimated through the NEIGRIHMS website and only the candidates will be eligible for the interview. Shortlisted candidates must bring all the required documents (Original + sell attested photocopy- one) and one recent passport-size photograph. Candidates without the original certificates at the time of the interview will not be considered. - Date of interview: 24th April 2023 (Monday) from 09:00 AM - Venue: Seminar Room, Department of Community Medicine, Main Building, NEIGRIHMS, Shillong Advertisement No:– NEIGR/Commed/ICMR_HRQOL/2023/1 (Date: 11.04.2023) Those who wish to apply are advised to go through the below official notification in detail before submitting applications. Download Official Notification Click Here Application Link Click Here Read the full article

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What is AI, ML and DS? Future Scope and Skills

Although the phrases data science, artificial intelligence (AI), and machine learning are related and belong to the same field, they each have unique uses and definitions. Even though these domains can have overlaps, each of these three terms has a specific use. All 3 domains are an inclusive party of the curriculum offered by most colleges for B.Tech in Artificial Intelligence.  

Most B.Tech CSE Artificial Intelligence and Data Science courses discuss these differences in detail. This allows students to choose which domain they want to excel in. Best Colleges for B.Tech in Artificial Intelligence have subjects related to data science and machine learning in their curriculum to help students establish the similarities between as well as identify how they differ.

Let’s find out more about all 3 domains, their scope, and skill requirements.

What is Data Science?

You probably asked yourself, “What is Data Science?” Data systems and processes are the subjects of the large field of research known as “data science,” which aims to preserve data collections and derive meaning from them. To make meaning of seemingly random data clusters, data scientists utilize a variety of instruments, programs, theories, and algorithms. Monitoring and preserving this data is challenging because practically all enterprises worldwide produce exponential volumes of data. To keep track of the always-expanding data collection, data science focuses on data modeling and warehousing. Data science applications are used to extract information that is then used to direct company operations and accomplish organizational objectives.

B.Tech CSE in Artificial Intelligence and Data Science is a combined study of how these two technologies can help humans develop computers and machines that derive information from data and learn from them without human interactions.

Scope of Data Science

Business intelligence is one of the areas that data science has a direct influence on. Having said that, each of these roles has a certain job description. Large amounts of data are the main tool used by data scientists to examine patterns, trends, and other things. These analytic programs create reports that are ultimately useful for drawing conclusions.

A business intelligence specialist continues where a data scientist leaves off by employing data science reports to comprehend the data trends in any given business field and by offering business projections and courses of action based on these inferences. It’s interesting to note that the related subject of business analysis also uses applications for data science, data analytics, and business intelligence. To assist businesses in making data-driven decisions, a business analyst profile incorporates elements of both.

Numerous data-oriented tools, such as SQL, Python, R, Hadoop, etc., are used in B. Tech CSE in Artificial Intelligence and data science course study. To get meaning out of data sets, it also makes considerable use of statistical analysis, data visualization, distributed architecture, and other techniques.

Data scientists are knowledgeable individuals with the ability to swiftly change jobs at any stage of a project’s life cycle. They can operate equally well with AI and machine learning, and data scientists need to be skilled in machine learning for the following purposes:

Machine Learning for Predictive Reporting

Machine Learning for Pattern discovery

Popular jobs for B. Tech CSE in Artificial Intelligence and Data Science graduates

Data Scientist

Data Analyst

Machine Learning Engineer

Data Engineer

Big Data Engineer

Data Architect

Database Administrator

Business Intelligence Analyst

Statistician

Skills you will get in B.Tech CSE in Artificial Intelligence and Data Science

Some Data Science skills include:

Programming: R, Python, SQL, SAS, MATLAB, STATA

Data Wrangling: Cleaning, Manipulating, and Exploring Data

Data Visualization: Creating graphs and charts to visualize data

Data Analysis: Conducting statistical analyses of data

Machine Learning: Building algorithms to learn from data

How is Artificial Intelligence?

Artificial intelligence (AI) is one of the most common terms widely used in today’s era due to its rising popularity, and has come to be associated only with futuristic-looking robots and a society ruled by machines. In truth, artificial intelligence is far different from that.

Simply, artificial intelligence seeks to replicate human intelligence so that machines can perform reasoning. Since teaching machines through experience is the primary goal of AI processes, it is essential to provide accurate information and allow for self-correction. For machines to recognize patterns and inferences, AI experts rely on deep learning and natural language processing.

Best colleges for B.Tech in Artificial Intelligence emphasize real-time practical knowledge and practices to help students learn about the complex nature of this technology. They use Alexa, and Cortana AI systems to teach students the basics of AI modeling and its purposes.

Scope for B. Tech CSE in Artificial Intelligence

With AI, automation is simple: With AI, you may automate routine, high-volume processes by putting in place dependable systems that run programs frequently.

Intelligent Products: AI has the power to transform ordinary goods into cutting-edge goods. AI applications can advance technology when combined with conversational platforms, bots, and other intelligent machines.

Progressive Learning: AI systems are capable of teaching computers to carry out any required tasks. The algorithms function as classifiers and predictors.

Data analysis is critical because machines take in the data we feed them, making it crucial to find the right data set. Machine training is simplified by neural networking. Together all these technologies can help develop a machine that can imitate a human brain.

Graduates in B. Tech CSE in Artificial Intelligence and Machine Learning can find jobs in sectors including finance, IT, corporates, Government agencies, gaming, VR, etc.

Popular jobs for B. Tech CSE in Artificial Intelligence graduates

Software Engineer

Software Tester

Application Developer

Information and Multimedia Designer

Medical Information Scientist

Technology Developer

IT Specialist

Technical Consultant

Quality Analyst

Information Network Manager

Data Quality Analyst

Skills you will learn in B. Tech CSE in AI and ML

Some artificial intelligence skills include:

Data analysis

Pattern recognition

Machine learning

Natural language processing

Robotics

Predictive modeling

Computer vision

Expert systems

Neural networks

What is Machine Learning?

Machine learning is a branch of B. Tech CSE in artificial intelligence that refers to systems that automatically learn from experience and get better over time. The goal of this branch of AI is to give robots the ability to learn on their own, eliminating the need for programming. This is the common relationship between AI and machine learning.

In machine learning, patterns are found through watching and analyzing data or experiences, and then a reasoning system is built based on the conclusions. The numerous elements of machine learning consist of:

Supervised machine learning

Unsupervised machine learning

Semi-supervised machine learning

Reinforced machine learning

Scope for B. Tech CSE in AI and ML graduates

There are several opportunities worldwide in the fields of B. Tech CSE in AI and ML. The world is being shaped by countless innovations, and many more in this particular subject is still to be discovered. The career opportunities in this field are growing daily as artificial intelligence replaces manual labor on a global scale. Numerous students have been inspired by this trend to enroll in the best colleges for B. Tech artificial intelligence and machine learning programs in India.

Due to its promising and lucrative scope, the B.Tech CSE in AI and ML has become one of the most sought-after programs in the modern world. Since graduates from colleges for B. tech CSE in Artificial Intelligence and Machine Learning can find jobs in a wide range of fields and sectors, the prospects are endless. With a B.Tech CSE in AI and ML, students can develop a variety of job prospects by using their theoretical and practical skills.

Artificial Intelligence engineer

Machine Learning Engineer

Data Scientist

Research scientist

AI data analyst

Robotics scientist

Skills you learn from colleges for B. Tech CSE in AI and ML

Some machine learning skills include:

Ability to identify patterns in data

Ability to build models to make predictions

Ability to tune model parameters to optimize performance

Ability to evaluate models for accuracy

Ability to work with large data sets

Internet of Things IoT

Before we conclude our discussion, it is crucial to talk about yet another B. Tech specialization in Internet of Things, IoT. Internet of Things, in many ways, contributes to the rising influence of AI, ML, and DS technologies. They are inter-connected and required the same skills to pursue a career in B. Tech.

Jobs in Internet of Things

IoT security specialist. …

IoT network engineer. …

Cloud engineer. …

Software developer. …

IoT systems administrator. …

Web development engineer. …

IoT embedded systems designer. …

IoT solutions engineer.

Conclusion

Since artificial intelligence, machine learning, and data science programs are rampant among engineering aspirants, there are many private colleges for B. Tech CSE in Artificial Intelligence and machine learning who offer these specializations both in India and abroad. These domains have opened up several job options, services, and product industries, creating opportunities for young engineers.

FAQs

Q1. WHAT IS THE ELIGIBILITY CRITERIA FOR B. TECH CSE IN AI AND ML?

All applicants must clear 12th from the science stream with at least 55% marks in aggregate. Best colleges for B. Tech CSE in Artificial Intelligence also consider entrance exams like JEE Main.

Q2.  WHAT JOB ROLES IN AI AND DS?

Data Scientist

Data Analyst

Machine learning engineer

Data Engineer

Big Data Engineer

Data Architect

Q3. WHY SHOULD I STUDY AI AND ML?

It would be best for you to learn AI first if you want to enter industries like natural language processing, computer vision, or robotics that use AI.

Q4. WHICH COMPANIES ARE HIRING FOR AI AND ML ROLES?

Google

IBM

Facebook

Amazon

Philips

Snap deal

Microsoft

Accenture

Adobe

Lenovo

Intel

Samsung

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NEIGRIHMS Recruitment 2023: Research Officer, Project Technical, Project Assistant, Nurse & DEO Vacancy

NEIGRIHMS Recruitment 2023: North Eastern Indira Gandhi Regional Institute of Health & Medical Sciences, Shillong released an employment notification for the recruitment of various posts on a contractual basis for one year under the ICMR project "A Community-Based Study on Health-Related Quality of Life (HRQOL), Functional Status and Morbidity Profile among Elderly Persons Living in Rural Setting of Meghalaya". The last date for submission of the application will be April 20, 2023. 1. Post Name:- Research Officer- Scientist-B (Medical) - No of posts:- 1 (One) - Upper age limit:- 40 years. - Salary:- Rs. 61000/- per month - Essential Qualification:- Bachelors degree (MBBS/BDS/AYUSH) from a recognized institute with one year of experience OR Postgraduate degree in Community Medicine/ Geriatrics/ Psychiatry from a recognized institute. - Desirable:- # Research/ Clinical experience in Geriatrics/ Psychiatry # Ability to handle SPSS/STATA or other statistical software(s). # Experience in handling ICMR funded ad-hoc projects/ any other extramural project. 2. Post Name:- Project Technical Officer (Psychologist) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 32,000/- per month - Essential Qualification:– Bachelor’s degree in Psychology from a recognized institute with one year of work experience OR Master’s degree in Psychology from a recognized institute. - Desirable:- # Ph.D. in psychology # Experience in clinical assessment and use of various scales for neuropsychological assessment. # Experience in working at the community level. 3. Post Name:- Project Invest Assistant (Field Investigator) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 31000/- per month - Essential Qualification:- Graduate in Science/ relevant subject from a recognized institute with one year or work experience OR Master’s degree in the relevant subject from a recognized institute. - Desirable:- Experience in working at the community level and should be able to collect the relevant data. 4. Post Name:- Junior Nurse - No of posts:- 1 (One) - Upper age limit:- 32 years. - Salary:- Rs. 18000/- per month - Essential Qualification:- Graduate in Nursing (B.Sc Nursing) from a recognized institute with one year of work experience OR Master’s degree in Nursing from a recognized institute - Desirable:- Ability to handle Microsoft Office (Word, Excel, and PowerPoint). 5. Post Name:- Data Entry Operator (Gr. C) - No of posts:- 1 (One) - Upper age limit:- 35 years. - Salary:- Rs. 31000/- per month - Essential Qualification:- Intermediate OR 12 pass in Science stream from a recognized board or two years experience in Electronic Data Processing (EDP) work in any recognized organization. - Desirable:- Ability to handle Microsoft office (Word, Excel and Power Point). How to apply for NEIGRIHMS Recruitment 2023: Research Officer, Nurse, DEO? Interested and eligible candidates may submit their applications online through Google with the necessary information. The last date for submission of the application is 20th April 2023. Shortlisted candidates will be intimated through the NEIGRIHMS website and only the candidates will be eligible for the interview. Shortlisted candidates must bring all the required documents (Original + sell attested photocopy- one) and one recent passport size photograph. Candidates without the original certificates at the time of the interview will not be considered. - Date of interview: 24th April 2023 (Monday) from 09:00 AM - Venue: Seminar Room, Department of Community Medicine, Main Building, NEIGRIHMS, Shillong Advertisement No:– NEIGR/Commed/ICMR_HRQOL/2023/1 (Date: 11.04.2023) Those who wish to apply are advised to go through the below official notification in detail before submitting applications. Download Official Notification Click Here Application Link Click Here Read the full article