#SPSS assignment answers

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Unraveling Data Mysteries: A Beginner's Guide to SPSS Exploration and Analysis

Statistics plays a pivotal role as the bedrock of empirical research, offering priceless insights into the intricate relationships that exist among variables. Within the realm of graduate-level statistical analysis, we navigate the labyrinth of data using the robust Statistical Package for the Social Sciences (SPSS). Our primary objective is to unearth patterns and relationships among variables, amplifying our comprehension of the underlying data structures. Join us as we embark on an illuminating journey through two intricate numerical questions that not only challenge but also showcase the potential of SPSS in untangling the multifaceted complexities of statistical analysis. If you are seeking assistance or struggling with your SPSS assignment, rest assured that this exploration might provide the help with SPSS assignment you need.

Question 1:

You are conducting a research study to analyze the relationship between students' hours of study and their final exam scores. You collect data from a sample of 100 graduate students using SPSS. The dataset includes two variables: "Hours_of_Study" and "Final_Exam_Score." After importing the data into SPSS, perform the following tasks:

a) Calculate the mean, median, and mode of the "Hours_of_Study" variable.

b) Determine the range of the "Final_Exam_Score" variable.

c) Generate a histogram for the "Hours_of_Study" variable with appropriate bins.

d) Conduct a descriptive analysis of the correlation between "Hours_of_Study" and "Final_Exam_Score" variables.

Answer 1:

a) The mean of the "Hours_of_Study" variable is 15.2 hours, the median is 14.5 hours, and the mode is 12 hours.

b) The range of the "Final_Exam_Score" variable is 40 points.

c) The histogram for the "Hours_of_Study" variable is attached, indicating the distribution of study hours among the graduate students.

d) The correlation analysis shows a Pearson correlation coefficient of 0.75 between "Hours_of_Study" and "Final_Exam_Score," suggesting a strong positive correlation between the two variables.

Question 2:

You are conducting a multivariate analysis using SPSS to examine the impact of three independent variables (Variable1, Variable2, Variable3) on a dependent variable (Dependent_Variable). The dataset includes 150 observations. Perform the following tasks:

a) Provide the descriptive statistics for each independent variable (mean, standard deviation, minimum, maximum).

b) Conduct a one-way ANOVA to determine if there are significant differences in the mean scores of the Dependent_Variable based on the levels of Variable1.

c) Perform a regression analysis to assess the combined effect of Variable2 and Variable3 on Dependent_Variable.

Answer 2:

a) Descriptive statistics for each independent variable are as follows:

Variable1: Mean = 25.3, SD = 3.6, Min = 20, Max = 30

Variable2: Mean = 45.8, SD = 5.2, Min = 40, Max = 50

Variable3: Mean = 60.4, SD = 7.1, Min = 55, Max = 70

b) The one-way ANOVA results indicate a significant difference in the mean scores of Dependent_Variable based on the levels of Variable1 (F(2, 147) = 4.62, p < 0.05).

c) The regression analysis reveals that Variable2 and Variable3 together account for 65% of the variance in Dependent_Variable (R² = 0.65, p < 0.001), suggesting a substantial combined effect of these variables on the dependent variable.

Conclusion:

SPSS serves as a powerful tool for unraveling the intricacies of statistical relationships. From exploring correlations between study hours and exam scores to conducting multivariate analyses, our journey through these graduate-level questions demonstrates the versatility and depth that SPSS brings to statistical exploration. As we navigate the depths of data analysis, we gain valuable insights that contribute to the ever-evolving landscape of statistical research.

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What are the best thesis writing services?

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But not all services are created equal.

Some promise the moon and deliver recycled content. Others overcharge and ghost you when you ask for revisions. So how do you find a thesis writing service that’s actually worth your time and money?

Let’s break it down.

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You want real academic support—not just a writer who rephrases Wikipedia. That’s why services built by subject experts and academic professionals stand out. They know what your university expects and they’ve helped hundreds of students just like you.

Let’s talk about three of them.

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Imagine having someone who helps you pick the right topic, guides you through your literature review, runs your data analysis, and even formats your document the way your university wants it. That’s what All Homework Assignments is all about.

It’s best for students in management, nursing, education, psychology, and general academic fields. And yes, they’re super responsive—WhatsApp support is available 24/7, so you’re never left hanging.

2. Programming Online Help

Now, if your thesis involves coding, simulations, or anything technical, this is your go-to team.

Whether you’re working on a machine learning model in Python, building a Java-based project, or writing a CS dissertation, they’ve got the technical and academic skills to bring your vision to life. They don’t just help you write the thesis—they help you build it too.

3. Statistic Homework Tutors

Doing a thesis that’s heavy on numbers? Maybe you're analyzing survey results, running regressions, or testing hypotheses. That’s where Statistic Homework Tutors shine.

From SPSS to STATA to R, they handle the stats side so you don’t have to sweat over it. Great for students in economics, public health, finance, psychology, and other research-focused areas.

🚀 Why These Services Stand Out

Here’s what sets them apart from the random “write my thesis in 24 hours” sites you see floating around:

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They’re not the cheapest in the world, but they’re student-budget friendly, and what you get in return is actual peace of mind.

⚠️ Quick Tip Before You Choose Any Service

Ask these three questions:

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🎯 Final Thought: Your Thesis Deserves the Best

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[tutorsindia152]

USA Assignment Assistance – SPSS, Python, Writing Help & Full Academic Services

How Custom Assignment Help Services Drive Academic Success for USA Students

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From detailed research and writing to advanced SPSS analysis and programming help with Python, R, or MATLAB, our US-focused academic experts help you meet your university’s expectations and deadlines. Our services ensure your assignments are plagiarism-free, well-structured, and adhere to US academic standards.

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Data analysis support using SPSS, R, Python, and MATLAB for quantitative and mixed-methods research.

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[sathcreation]

Data Interpretation Assignment Help: Complete Guide to Scoring High with Expert Support

Introduction

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Whether it's a college project or an online course task, our experts simplify the process so you can learn while you complete your work. Every assignment is handled by professionals who ensure clarity, accuracy, and academic excellence.

About Gritty Tech Academy (150 Words)

Gritty Tech Academy is a trusted name in academic support. With a team of highly experienced educators and data analysts, the academy focuses on helping students across the globe succeed in technical and analytical subjects. What sets us apart is our commitment to personalized learning.

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Accurate and Affordable Statistics Assignment Help for Students

Need reliable statistics assignment help ? Our expert statisticians provide accurate, plagiarism-free solutions tailored to your academic needs. Whether it’s probability, regression, hypothesis testing, or data analysis using tools like SPSS, R, Excel, or Python—we’ve got you covered. We deliver well-explained answers, on-time submissions, and 24/7 support to help you meet deadlines and boost your grades. Trusted by students worldwide, our statistics assignment services are affordable, confidential, and designed for academic success. Get the professional help you need—contact us today.

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The Power of Quantitative Methods in Modern Research

In an era where data is considered the new oil, quantitative methods have emerged as the backbone of credible, data-driven research. These methods transform raw numbers into meaningful insights, helping professionals across various sectors make informed decisions with confidence.

Why Quantitative Methods Matter

Quantitative methods are essential because they bring structure and precision to the research process. By using numerical data, these methods allow for clear measurement, comparison, and statistical validation. This reduces the risk of bias and ensures that results can be replicated and scaled.

Whether you're working in business, academia, public policy, or technology, quantitative methods help answer key questions such as:

What is happening?

How often does it happen?

Is there a correlation or causal relationship?

Types of Quantitative Methods

Descriptive Research Used to summarize and describe features of a dataset. It includes frequencies, percentages, averages, and more.

Correlational Research Investigates the relationship between two or more variables without manipulating them.

Experimental Research Involves controlled experiments to establish cause-and-effect relationships.

Quasi-Experimental Research Similar to experimental research, but without random assignment—often used when true experiments are not feasible.

Tools and Techniques

Professionals using quantitative methods often rely on tools such as:

SPSS, R, or Python for statistical analysis

Excel for data entry and visualization

Surveys and structured questionnaires for data collection

They also use techniques like hypothesis testing, regression analysis, and factor analysis to interpret results.

Real-World Impact of Quantitative Methods

In marketing, they reveal consumer behavior trends and campaign performance.

In education, they help assess the effectiveness of teaching methods.

In healthcare, they guide treatment decisions based on clinical trial data.

In government, they shape public policy through population studies and economic forecasts.

Conclusion

The ability to harness and interpret data through quantitative methods is no longer optional—it’s a necessity. These methods provide clarity, credibility, and actionable insight in a world overflowing with information. Whether you're a student, researcher, or professional, building strong skills in quantitative methods is a smart investment in your future.

[statistics-homework-helper]

🌸 Spring Into Success: Get 10% Off Your Statistics Homework Today!

As the season changes and a fresh wave of motivation fills the air, it’s the perfect time to shake off academic stress and step confidently into success. Spring is often seen as a season of renewal—and for students, it’s a chance to reset goals, reevaluate priorities, and refresh academic strategies. If statistics has been weighing you down, we’ve got just the solution to help you blossom this season. At StatisticsHomeworkHelper.com, we’re offering 10% OFF your next assignment when you use the referral code SHHR10OFF. Whether you're stuck on a regression analysis, hypothesis testing, or probability distribution, our statistics homework help service is designed to guide you every step of the way.

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Why Statistics Remains a Challenge for Many

Statistics can be one of the most misunderstood subjects in a student's academic journey. The challenge lies not just in crunching numbers, but in interpreting data correctly, understanding probability concepts, and drawing accurate conclusions. For students unfamiliar with real-world applications, the theoretical nature of topics like ANOVA, Chi-square tests, and correlation coefficients can become daunting.

Another reason statistics becomes overwhelming is the pressure of deadlines. Coursework tends to pile up quickly, especially in semesters filled with multiple quantitative subjects. Students often feel like they have no room to breathe, let alone grasp intricate statistical techniques.

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With years of experience serving students across the globe, we’ve refined our services to ensure they meet your academic needs while staying budget-friendly. Here’s what you can expect from us:

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Help with Statistics Homework to Build Confidence in Stats Class

Statistics is an essential course for all disciplines including business, social science, engineering, and data science. Statistics, in particular, is among the most difficult subjects that many students struggle with. Challenges often arise from its mix of theoretical and practical aspects of the subject, mathematical computations involved, and precision needed in the analysis of data. It is not easy to develop confidence in statistics, but with the right approach, tutorials, resources, and change of mindset it is possible to master statistics rather than to fear it. In this article, you will discover how students can increase their confidence in statistics class by seeking the right help with statistics homework and how quality assistance can keep them one step ahead.

Why Statistics Feels Intimidating and Why Confidence Matters 

Statistics is intimidating for many students, often due to a few core challenges:

Complexity and Abstract Concepts: Statistics involves abstract thinking which is more complex than algebra or calculus, requiring proficiency in concepts such as probabilities and statistical modeling. Most students often find it difficult to identify which statistical tests to use, or when to use a t-test instead of an ANOVA or comprehend what p-values and confidence intervals interpret.

Data Analysis Requirements: When it comes to statistics the goal is not to solve a problem, but to analyze and interpret data accurately. In the case of students who are not conversant with data manipulation tools such as Excel, SPSS, or R this can be very challenging. Application of these software tools creates an added level of difficulty making it more challenging for students to carry out their analysis.

Pressure of Application: Statistics indeed has a purpose and is not just limited to classroom teaching. It requires students to apply knowledge in solving difficult, real-life issues. It can be intimidating at times, and that’s pretty understandable because there isn’t usually a single correct answer, but rather different perspectives and interpretations based on data.

Due to these difficulties, statistics hinder the confidence of even the most disciplined learners. Due to lack of confidence, may result in procrastination, reduced performance as well as a tendency to not seek assistance from other fellow students and professors. Utilizing the right resources and guidance, students can regain confidence and develop a strong foundation in statistics.

The Role of Homework Help in Building Confidence

To obtain confidence in a statistics class one of the best things to do is to get reliable experts for high-quality help with statistics homework. Expert homework assistance goes a long way when it comes to simplifying complex topics, explaining confusing concepts, or demonstrating solutions that mimic real-life problems. Here’s how it can transform a student's learning experience:

1. Focus on Tough Topics: A tutor or homework service can give explanations that match the grasping power of a student. The solutions provided by homework help experts are self-explanatory which becomes easier for students to grasp. Difficult topics are broken down into manageable parts for easy understanding and make it engaging for students. 2. Practice with Feedback: Practicing problems along with instant feedback is critical for mastering statistics. Most assignment help services provide guidance at every step along with helpful feedback to the students to see where they are wrong and advice on suitable methods to use. 3. Application of Statistical Software: Learning advanced stat software like R, SPSS, or Python is always a challenge for beginners. Assignment help services can teach students how to use them properly, with hands-on examples of coding and choosing the right statistical methods. 4. Improved Time Management and Stress Reduction: Solving statistics homework involves a lot of time and energy. With guided assistance, students are able to solve problems faster, and with less confusion thereby cutting down time and work overload. This helps them to be able to keep up with their coursework.

Our service is aimed at students who have difficulties with completing their statistics homework on their own. Here students can find helpful resources on basic and advanced statistical methods, and analysis tools, as well as useful tips for solving problems. All in all, students not only get their assignments done but also receive useful information that can help them build confidence in the subject.

Key Strategies for Building Confidence in Statistics Class 

Besides using homework help, students can take specific actions to help herself or himself. Here are some effective strategies that can make a significant difference:

1. Understand the Basics Before Solving a problem

Indeed, statistics as a subject has a foundational structure; understanding the basic concepts first paves way for handling advanced concepts. Some of the key basic topics that are essential are descriptive statistics (arithmetic mean, geometric mean, standard deviation) probability/probabilities, and basic probability distributions. By mastering these basic concepts, students are in a good position to learn more complicated concepts like Inferential statistics and regression analysis.

A good source to sharpen your basic statistics knowledge is – “Statistics for Dummies” by Deborah Rumsey, this book breaks down essential statistical concepts in an easy-to-understand manner.

2. Use Reliable Resources and Textbooks 

Good textbooks and resources provide clarity.” Some highly recommended textbooks for students learning statistics include:

• “The Essentials of Statistics” by Mario Triola: This textbook is favored in statistics courses, as the author presents all concepts in a clear and understandable manner for students to succeed in class.

• “Applied Statistics and Probability for Engineers” by Douglas C. Montgomery: This book should come in handy to engineering students and it contains real-life examples and applications.

• “Introduction to the Practice of Statistics” by Moore, McCabe, and Craig: An encyclopedic book that also features practical examples thus recommended for students in the social and natural sciences.

3. Practice with Real Data

Using real datasets can help to make statistics much more interesting. Students can sharpen their data analysis skills by practicing with the datasets that belong to their field of study. Kaggle has free datasets for all types of projects and domains so that students can execute statistical tests on real datasets and analyze the impact of their analysis.

4. Develop a Strong Support System 

Studying with friends in a group provides additional support and motivation. Students can easily study groups to solve problems, exchange ideas, and perspectives, and study material. Moreover, there are many forums and communities available online where students can join and get guidance and advice from experienced statisticians.

5. Seek Help Early and Consistently 

This is one of the most common mistakes that students make is waiting until the last minute to complete their assignments. Engaging with homework helps experts prevent last-minute panic and enables students to strengthen their conceptual knowledge gradually and at the same time identify weak areas. This helps build confidence.

Our Statistics Homework Help Service: Building Confidence Step-by-Step 

For students who are in need of help with statistics assignments, our homework help service provides a reliable medium. We offer:

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More Teaching Aid and Assistance for Statistics Students

To supplement further help with statistics homework, here are some additional tools and resources students may find useful:

•StatCrunch: An online tool to perform statistical analysis with simple and versatile tools.

•Wolfram Alpha: An application or software that can handle statistical problems and provide a step-by-step explanation of how it was solved.

•YouTube Channels: There is no shortage of channels with good statistical video tutorials available on YouTube showing step-by-step examples of approaching and solving a problem pr performing statistical processes in software like R, SPSS, SAS, Eviews, etc.

Conclusion: Embrace the Journey to Mastery in Statistics

Though statistics may seem very daunting at first, with the right support and will, any student can master this important area of academics and mold themselves into confident statisticians. Getting confidence in statistics is a blend of grasping the fundamental concepts combined with continuous consistent problem-solving and having reliable expert support that can be counted upon for assistance whenever needed. Whether through our homework help service, recommended textbooks, or any additional resource, students can get over their fears, creating a definite pathway to success in statistics.

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My Lifesaver for Statistics: A Testimonial on statistics homework helper

As a student juggling multiple courses, finding time to focus on each assignment can be a daunting task. This semester, I found myself particularly challenged by my statistics class, especially when it came to using SPSS for my homework. Thankfully, I discovered statisticshomeworkhelper.com, which became my go-to solution for help with SPSS homework and other statistical assignments. Here’s my journey and experience with this incredible service.

The Overwhelming Challenge

Statistics is a subject that can be both fascinating and frustrating. The theories and principles are intriguing, but the practical application, especially using software like SPSS, can be intimidating. This semester, I was assigned a comprehensive project that required extensive data analysis using SPSS. Despite attending all my classes and going through the tutorial sessions, I found myself lost and overwhelmed by the complexity of the software and the intricacies of data interpretation.

I spent hours trying to figure out how to run various tests, analyze the results, and present my findings in a coherent manner. The more I tried, the more frustrated I became. It was clear that I needed help – professional help.

Discovering statisticshomeworkhelper.com

One late night, while browsing for solutions online, I stumbled upon statisticshomeworkhelper.com. The website promised expert assistance with statistical assignments, including detailed help with SPSS homework. The testimonials from other students were overwhelmingly positive, and the services offered seemed to be exactly what I needed.

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SPSS Assignment Help Strategies on Handling Missing Data

Missing data is a common issue in statistics as well as data science. Handling it correctly is important to make sure that your analysis is accurate and reliable. This post gives detailed methods for dealing with the missing data with the use of SPSS, specifically for the students studying statistics or data science. We will explain the different techniques, show examples, as well as mention important books and papers. Additionally, we will introduce our SPSS analysis assignment help tips for assisting students with their data analysis tasks.

Types of Missing Data

Missing Completely at Random (MCAR): The chances of data being missing are completely random as well as not influenced by any other data. For example, any survey response might be missing because the person accidentally skipped the question, and this has nothing to do with their age, gender, or any other characteristic.

Missing at Random (MAR): The likelihood of any data being missing is related to the observed variables. For instance, if women are less likely of answering any certain survey question, the missing data depends on gender, which is known, but not on anything unknown.

Missing Not at Random (MNAR): Data is missing for reasons that is related to the unobserved variables. For example, people might not report their income because it is very high or very low, and this missing data is related to the income level, which is not observed.

Strategies for Handling Missing Data in SPSS

Listwise Deletion

Listwise deletion removes any data entries with the missing values. It is simple as well as easy to use, and it keeps your analyses consistent. However, it helps in reducing the sample size, which can weaken your results. It also assumes the missing data is completely random, which is often not correct. In SPSS, you can use listwise deletion by choosing "Exclude cases listwise" under the "Missing Values" tab.

Example: Consider a dataset with variables A, B, and C. If a case has a missing value in any of these variables, the entire case is excluded from the analysis.

Pairwise Deletion

Pairwise deletion only excludes data entries with missing values for the specific analysis being done, using as much of the available data as possible. In SPSS, you can apply pairwise deletion by selecting "Exclude cases pairwise" under the "Missing Values" tab. The benefits of this method include using more data than listwise deletion and being useful for large datasets with random missing data. However, it can lead to inconsistencies across different analyses and assumes the missing data is either completely random or related to known factors.

Example: If a case has missing values in variable C but not in variables A and B, the case is included in the analysis of A and B.

Mean Imputation

Mean imputation replaces missing values with the mean of the observed values for that variable. To do this in SPSS: Go to "Transform" > "Replace Missing Values," select the variable, and choose "Mean" as the method. This approach is simple and keeps the sample size intact. However, it underestimates variability and can distort relationships between variables, and it assumes the missing data is completely random.

Example: If the mean of variable A is 10, all missing values in A are replaced with 10.

Multiple Imputation

Multiple imputation creates several datasets by guessing missing values with a range of possible numbers, then merges the results. To do this in SPSS: Navigate to "Analyze" > "Multiple Imputation" > "Impute Missing Data Values," and indicate the number of guesses and the variables to be filled. This method considers the uncertainty in missing data, offering better parameter estimates and errors. However, it is more complicated and takes more computationally intensive, and it relies on assumptions about how the data is distributed.

Example: Create five datasets with different imputed values for variable A and combine the analysis results.

Regression Imputation

Regression imputation predicts missing data by assessing other dataset variables. In SPSS, you can do this by heading to "Transform" > "Replace Missing Values," picking the variable, and selecting "Regression" as the method. It’s helpful because it uses existing data to make better guesses and keeps the connections between numbers intact. However, it assumes that the relationships between the numbers are straight lines and might not capture all the differences accurately.

Example: Predict missing values in variable A using variables B and C as predictors.

Computational Illustrations in SPSS

Let's illustrate mean imputation using a simple example. Suppose you have a dataset with missing values for the variable "Age":

AGE

25

.

32

28

.

In SPSS, you can use the "Replace Missing Values" function under the "Transform" menu to replace the missing values with the mean age:

Go to Transform > Replace Missing Values.

Select the variable "Age" and move it to the "New Variable(s)" box.

Choose "Series Mean" as the imputation method.

Click "OK."

SPSS will create a new variable with the imputed values.

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Contact us today to for SPSS homework help and let us help you overcome the challenges of missing data!

Recommended Textbooks and Papers

Textbooks:

. Applied Missing Data Analysis by Craig K. Enders

. Statistical Analysis with Missing Data by Roderick J.A. Little and Donald B. Rubin

Papers: Schafer, J.L., & Graham, J.W. (2002). "Missing Data: Our View of the State of the Art."

[realyoungdarius]

Lab assignment 1

This week, we start using SPSS. The assignments are getting less labor-intensive, as you will get the mathematics for free. Still, you should always keep in mind that software can only help you if you understand what they do and in which case you can use this or that function.

SPSS stands for Statistical Package for the Social Sciences, and is the most frequently used software among psychologists, sociologists and linguists (and probably in many other fields) to perform statistical computations.

Although you create a report, you do not need to turn this in unless you are taking the course for credit. We will discuss how to write up statistical results, and it may be useful to exchange the reports with other students in order to get some criticism.

In general reports should be as short as possible, that is, copy-and-paste only the SPSS results that are necessary. Explain the results in one sentence, especially if you needed to do more than just copy-paste (e.g., find the lowest value or calculate the difference of two values). Do not add any further information. Reporting irrelevant information can result in less points, as filtering the relevant information is one of your tasks.

Tasks that you simply have to do (before you get to the questions) appear below with a > starting the line in bold letters. Concerning these, you need not report anything, simply perform these tasks. The questions to be answered in the report are given below with a * starting the line, and in bold letters.

Answer the questions in a short but exact way, starting the number of the question. For instance:

… 3. 20 measurements. 4. Word length 3. …

Try to finish all assignments during the lab. Should this fail, you can go on working on the assignments in your own time.

Aims of Lab 1

A     Getting familiar with SPSS

B1    Entering data by hand

B2    Using “Variable View”

B3    Creating a frequency table

C     Creating a histogram

D     Creating a boxplot

E     Calculating mean, modus and median

F     Calculating measures of spread

Lab 1

A. Getting familiar with SPSS

> Turn on computer and screen. > Enter username and password to log in. > Look up SPSS 14 (etc.) within the RUG menu (within Mathematics & Statistics) and launch SPSS.

In case SPSS has not been installed on your machine yet, you get a window saying that you have to restart your computer. Do that, otherwise SPSS may have problems running.

> Once SPSS is running, you are offered a menu with choices. Click on “cancel”.

Now you are in the Data Editor, the window of SPSS in which you can enter data and work on them. It is a spreadsheet you might be familiar with from other applications. On its top you find the name of the data file you are working with, but at this moment it is still: Untitled1 [DataSet0].

In the Data Editor, each (vertical) column of numbers represents a variable. Each variable is given a name, which appears on the top of the column. Use meaningful names, such as LENGTH, and not something like X24A06.

Each (horizontal) row represents a case. A case is a series of observations belonging together, such as the answers of a respondent to the questions in a questionnaire, or different values measured on the same subject of the experiment. For instance, if you have 32 respondents, then you need 32 rows for the 32 cases. If the questionnaire contained 40 questions, then you most probably need 40 columns, and so you have 40 variables.  (Next week, we learn how to calculate new, derivative variables from existing ones.)

The Data Editor is composed of two parts: the Data View and the Variable View. By clicking on the knob on the bottom left part of the page you can switch between them.

The Variable View offers an overview of your variables, and you can also define some features of these variables. The most important features are:

1. Name: the name of the variable. 2. Type: defines the type of the variable. Some of the types offered by SPSS: 3. Width: the number of positions available in the Data View window. 4. Decimals: the number of decimal digits after the comma/dot. 5. Label: text providing more information about the variable. 6. Values: texts providing information about each value of the variable. 7. Missing: the value used to denote missing values (e.g., “no answer”). 8. Column: the width of the column in the Data View window. 9.Measure: the “measurement scale” of the variable (nominal, ordinal or scale, the last covering all types of numeric scales).

On the top of the window you find the menu of SPSS: FILE, EDIT, VIEW, DATA, etc. All statistical calculations are found under ANALYZE, and all diagrams and charts under GRAPHS. To calculate new variables based on the existing ones, use the commands under TRANSFORM. The HELP menu provides you help with further assistance, but which may prove quite concise in the beginning.

> Have a look at the different menus to get a general overview of them.

B. Entering data and creating a frequency table

The MLU (Mean Length of Utterance) measures the length of an utterance (a well-formed sentence or a sentence-like series of words) by counting the number of words it contains. It is an important measure of linguistic capabilities of children acquiring a language, of patients with impaired language, but it is also useful in identifying authors of texts.

Here are the lengths of test utterances produced by 20 patients:

3, 5, 4, 4, 10, 4, 11, 4, 4, 6, 3, 4, 4, 8, 8, 8, 5, 8, 4, 9.

> Enter these values by hand and add the variable the name MLU. > In the Variable View, set the number of decimals to 0 (as utterence length always has an integer value).

When you work with SPSS (as with any other application), it is good practice to regularly save your data files. Output files are often simpler to create again, but data files are certainly not. Moreover, SPSS 14 is not always stable, causing the program to terminate unexpectedly. Finally, we may want to use some of the data files during several labs.

> Therefore, save your data file to your own network drive (X:\) in a separate folder that you create specifically for this lab.

A frequency table is a table that shows how often each value of a variable appears among your data.

> Create a frequency table from this variable. Hint: 'Analyze', 'Descriptive Statistics', 'Frequencies'.

During the data entry process, one quite often makes errors. Hence, it is imperative to check always the data you have just entered. Beside rereading the numbers in Data View, you should also look for outliers “created” by erroneous data entry:  for instance, typing too many zeros or entering two values in a single cell will create values much greater than other values. In the present case, check if the frequency table contains only values you remember having entered (and that make sense). Compare also your frequency table to the one of your neighbours in the lab.

> Check the frequency of each value in your frequency table together your neighbour.

* 1. Copy the table in your report. * 2. How many measurements (data) do you have? * 3. Which MLU is the second most frequent? * 4. How often does the highest value of MLU occur?

C. Creating a histogram

A histogram (or frequency diagram) is a graph displaying how frequently each of the possible values of a variable occur (or how frequently values falling within a certain range occur) among the data having been entered.

> Create a histogram based on the variable MLU. Hint: 'Graphs', 'Histogram'.

> Do it again, but have SPSS also draw a Normal curve. Hint: mark the checkbox ‘display normal curve’.

* 5. Copy this second graph to your report. * 6. What does the vertical axis display: numbers or percentages? * 7. What is the highest value and what is the lowest value of the variable? * 8. How many peaks are there? * 9. There is a gap is the graph. At what value can this gap be found? What does this observation mean? Would you expect to find this gap if you had many more data? * 10. Is this distribution approximately Normal?

D. Creating a boxplot

A boxplot is another visualization of a distribution and it proves useful for other purposes later on.

> Create a boxplot of your variable.

Hint: 'Graphs', 'Boxplot'. Choose: “Simple” and “Summary separate variable”.

* 11. Copy this boxplot to your report. * 12. Which is the lowest and highest value according to the boxplot? * 13. Which is approximately the median according to the boxplot? * 14. How many percentages of the data are outside of the box? * 15. Which data are outside of the “whiskers” of the boxplot?

E. Calculating mean, modus and median

We often would like to summarize a variable as a single number that tells you roughly where the values of that variable are located. Generally the mean (average) is used for that purpose. Another option is employing the modus, that is, the value that appears most frequently. One can also use the median, the middle value if the observations are sorted from lowest to highest.

When a histogram is created, the mean is automatically calculated. The modus, the median and the mean can also be derived by choosing “Analyze”, “Descriptive Statistics”, and then “Frequencies“ in the menu. If you wish, uncheck the mark next to ‘Display Frequency Table’, and ignore the warning. Then choose the mean, the modus and the median via the Statistics.

> Have SPSS calculate the mean, the modus and the median, and report them to you in a single table.

* 16. Copy this table to your report. * 17. Suppose you make an error during data entry: you type 80 instead of 8. Which of these values will change, and which will not? (Why? How does M&M call this feature of a statistical measure?) * 18. The median of MLU is lower than its mean. This is because the histogram is skewed to the … (left or right?), and it has a longer tail to the … (left or right?).

F. Calculating measures of spread

In many cases we are not only interested in where more or less the values of the variable are located, but also in the “width” of the frequency distribution. There are different measures of describing the “width” of the histogram. The most known one is standard deviation (SD), but range and interquartile range are also used. The drawback of the range (the difference of the maximum and minimum values) is that it is fully dependent on the two most extreme values being measured.

> Have SPSS calculate for you the SD, the range and the quartiles. Hint: “Analyze”, “Descriptive Statistics”, “Frequencies”.

* 19. Report the SD, the range and the IQR. * 20. If the range is seen as the width of the histogram, then how many SD is the width of this histogram? (How many times is the range larger than the SD?)

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SPSS Assignment Help – Your Reliable Academic Partner

Introduction

Students often face difficulties while handling statistical software tasks, especially those involving SPSS (Statistical Package for the Social Sciences). If you're struggling with complex data analysis, interpreting results, or submitting your assignment on time, our SPSS Assignment Help is here to assist For More...

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