#Random Variable and Distribution Function Assignment Help Random Variable and Distribution Function Project Help Random Variable and Distrib | Explore Tumblr posts and blogs

scentedbeardgarden · 4 years ago

Quote

Business Analyst course

Many kids are aspiring to come across a career transition into these roles. Let us look into a couple of of the main job positions of the Data Science area. Big knowledge refers to massive amounts of information from numerous sources from totally different formats. Big information revolves across the data that cannot be dealt with by the traditional data analysis method. It is related to many business sectors like IT services, healthcare and e-commerce industries, banking and finance sectors, consultancy services, transport sectors, manufacturing models, etc. Data collection is considered as another major responsibility of a data scientist.

Data science consists of, along with ML, statistics, advanced knowledge analysis, knowledge visualization, information engineering, and so on. This is our superior Big Data coaching, the place students will gain sensible skill set not solely on Hadoop in detail, but additionally learn advanced analytics ideas by way of Python, Hadoop and Spark. For in depth hands-on practice, college students will get a quantity of assignments and initiatives. At end of this system candidates are awarded Certified Big Data Science Certification on profitable completion of tasks that are supplied as a part of the training.

To establish the properties of a steady random variable, statisticians have outlined a variable as a standard, studying the properties of the standard variable and its distribution. You will be taught to check if a steady random variable is following regular distribution utilizing a standard Q-Q plot. Learn the science behind the estimation of value for a population using pattern knowledge. Whether it is a fresher or someone with work expertise, everyone is making an attempt to get a share of this dawn sector. Majority scholars and professionals no matter their backgrounds are upskilling themselves to be taught the this course. The frenzy created out there has made us consider that anybody can turn out to be a Master of Data Science. One of the just lately launched Data Science course in India by Henry Harvin has been aptly named — Certified Data Scientist.

Business Analyst course

From analysing tyre efficiency to detecting problem gamblers, wherever information exists, there are opportunities to use it. Alongside these classes you will also research independently finishing coursework for each module. You will be taught through a sequence of lectures, tutorials and many sensible classes serving to you to increase your specialist data and autonomy. This module aims to introduce you to the basic idea of computing-on-demand resulting in Cloud computing. Emphasis is given to the different technologies to build Clouds and how these are used to supply computing on-demand. Full time college students might take an internship route, in which they are given an extra three months for an internship-based Project.

The course is aimed to develop practical enterprise analytics abilities within the learners. As this is an advanced-level knowledge analytics course, data analytics experience is obligatory to get started with the identical. The course would provide you with a deep understanding of superior excel formulation and functions to remodel Excel from a fundamental spreadsheet program into a strong analytics software. The course would additionally implement practical implementation by exercising contextual examples designed to showcase the formulation and how they are often applied in numerous ways. By the tip of the course, you may be trained to construct dynamic tools and excel dashboards to filter, show, and analyze knowledge. You may even be eligible to automate tedious and time-consuming tasks utilizing cell formulation & capabilities in excel. The course provided by Coursera educates learners concerning the numerous knowledge analytics practices involved with enterprise administration and growth.

An introduction to likelihood, emphasizing the combined use of arithmetic and programming to unravel issues. Use of numerical computation, graphics, simulation, and computer algebra. to statistical ideas including averages and distributions, predicting one variable from one other, association and causality, likelihood and probabilistic simulation. In some cases, students might complete different programs to fulfill the above stipulations. See the lower-division requirements web page on the Data Science program website for more details. No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired expertise, in the lengthy run, to a profitable profession in Data Science.

If you've any questions or issues, please contact and/or report your expertise via the edX contact type. HarvardX requires people who enroll in its programs on edX to abide by the terms of the edX honor code. No refunds shall be issued within the case of corrective action for such violations. Enrollees who're taking HarvardX programs as a part of another program may even be governed by the educational policies of those programs.

Data scientists primarily cope with huge chunks of data to analyse the patterns, tendencies and extra. These evaluation purposes formulate stories which are finally helpful in drawing inferences. Interestingly, there’s also a related subject which makes use of both information science, data analytics and enterprise intelligence applications- Business Analyst. A enterprise analyst profile combines slightly little bit of each to assist corporations take information driven decisions. The mission of the Ph.D. in hospitality enterprise analytics program is to offer advanced training to students in data science because it relates to the hospitality business. The aim is to arrange college students for highly demanding educational and analysis careers in top‐ranked establishments. Our faculty conduct in-depth analysis in various areas of research that apply to hospitality enterprise analytics, such as revenue management, digital marketing, finance, buyer experience administration and human sources administration.

These embody both free assets and paid information science certificate packages which are delivered online, are widely recognised and have benefited hundreds of students and professionals. With being increasingly utilized in a number of industries, information science is quickly turning into one of the fastest-growing fields. The learning platform edX has compiled a series of over 200 courses created by prime academic and industrial establishments to assist your studying. Pick a programming language that you are snug with and get began with analyzing huge chunks of datasets. You can reach us at: ExcelR- Data Science, Data Analytics, Business Analytics Course Training Bangalore Address:49, 1st Cross, 27th Main, Behind Tata Motors, 1st Stage, BTM Layout, Bengaluru, Karnataka 560068 Phone: 096321 56744 Directions: Business Analyst course Email:[email protected]

0 notes

360digitmgba · 4 years ago

Text

On-line Information Science Programs

Data Science project administration methodology, CRISP-DM will be explained on this module in finer detail. Learn about Data Collection, Data Cleansing, Data Preparation, Data Munging, Data Wrapping, and so forth. Learn in regards to the preliminary steps taken to churn the info, known as exploratory information analysis. In this module, you are also introduced to statistical calculations that are used to derive info from information.

You will implement algorithms corresponding to Principal Component Analysis and Naive Bayes after information evaluation to foretell the approval fee of a loan utilizing numerous parameters. This is an inventory administration project where you can see the tendencies within the knowledge that will help the corporate to extend sales.

I had taken the Data Science master’s program, which is a combo of SAS, R programming language, and Apache Mahout. Since there are such a lot of technologies involved in programs, getting our query resolved on the right time turns into an important aspect. But with Intellipaat, there was no such downside as all my queries were resolved in lower than 24 hours. I signed up for Intellipaat's Data science course on-line certification when I realized that it is an excellent spot for learning new applied sciences. The trainer of this course was actually good and helped me be taught the subject well. Besides, the net support group helped me to resolve any technical concern I had. I need to discuss in regards to the wealthy LMS that Intellipaat’s Data Science packages provided.

Intellipaat actively provides placement help to all learners who've successfully accomplished the training. For this, we are exclusively tied-up with over eighty top MNCs from around the globe.

Learn introductory programming and information analysis in MATLAB, with functions to biology and medicine. These certificates could be very well recognized in Intellipaat-affiliated organizations, together with over eighty top MNCs from all over the world and a few of the Fortune 500companies. At Intellipaat, you possibly can enroll in either the trainer-led on-line training or self-paced coaching.

The Boosting algorithms AdaBoost and Extreme Gradient Boosting are discussed as a part of this continuation module You will also learn about stacking methods. Learn about these algorithms which are providing unprecedented accuracy and helping many aspiring knowledge scientists win the primary place in various competitions similar to Kaggle, CrowdAnalytix, and so on. You have learnt about predicting a steady dependent variable. As a part of this module, you'll continue to learn Regression strategies utilized to predict attribute Data.

There are totally different slots out there on weekends or weekdays based on your decisions. We are also available over the decision or mail or direct interplay with the trainer for active learning.

In this tutorial you will study joint likelihood and its functions. Learn the way to predict whether or not an incoming e-mail is spam or ham e mail. Learn about Bayesian chance and the functions in solving advanced business problems.

It was an excellent session and got a fundamental thought of how AI is being used in analytics these days. After the end of the session, I was glad to join the Data Science program.

Data Science helps in combining the disruption into classes and communicating their potential, which permits information and analytics leaders to drive better outcomes. Top companies thought there's a necessity to investigate the info for important benefits. The trainers of the Data Science course are the trade's main specialists who've 15+ years of experience.

Universities have been slow at creating specialized information science programs. It is difficult to accumulate the talents necessary to be employed as an information scientist.

They hail from multinational firms like Microsoft, Google, L&T, Cognizant, and so forth. The trainers listed below are the spine of the Data Science coaching wing. This has caused an enormous demand and supply hole, where they hunt for knowledge scientists is relentless, and the provision for which is the naked minimum. Develop abilities in digital research and visualization techniques across topics and fields within the humanities. Click the “Buy Now” button and become part of our knowledge scientist program at present. Moreover, our focus is to show subjects that circulate smoothly and complement one another. The course teaches you everything you should know to become an information scientist at a fraction of the cost of conventional applications .

Apart from this, Intellipaat additionally provides corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant trade experience, and they have been actively working as consultants in the same area, which has made them material specialists. Go by way of the sample movies to check the quality of our trainers.

Kaplan Meier methodology and life tables are used to estimate the time before the occasion occurs. Survival analysis is about analyzing this period or time earlier than the occasion. Real-time purposes of survival evaluation in buyer churn, medical sciences and other sectors is mentioned as a part of this module. Learn how survival analysis techniques can be used to understand the impact of the options on the occasion using Kaplan Meier survival plot. Revise Bayes theorem to develop a classification approach for Machine studying.

youtube

The assist group has all the time been supportive and efficient to help us. The collaboration of sensible with theoretical information makes intellipaat highly appropriate for many who want to improve their profession. Use knowledge exploration to be able to understand what needs to be carried out to make reductions in customer churn. In this project, you'll be required to extract particular person columns, use loops to work on repetitive operations, and create and implement filters for data manipulation. In this project, you should work with a number of operators concerned in R programming together with relational operators, arithmetic operators, and logical operators for numerous organizational wants. In this project, you will use the banking dataset for data analysis, knowledge cleansing, information preprocessing, and data visualization.

We will begin to know tips on how to carry out a descriptive analysis. Join 360DigiTMG for the most effective Data Science Course in Hyderabad and turn out to be a professional Data Scientist with hands-on experience on real time initiatives in just four months.360digitmg offers the most effective Data Science certification online training in Hyderabad together with classroom and self-paced e-studying certification programs. The complete Data Science course particulars could be found in our course agenda on this web page. I even have attended a webinar given by IBM’s Senior Expert Mr G Ananthapadmanabhan (Practice chief – Analytics) on Emerging developments in Analytics and Artificial Intelligence.

You shall be using a V7 predictor, V4 predictor for evaluation, and information visualization for locating the probability of prevalence of fraudulent actions. The best online coaching heart, with a lot of hands-on tasks. One of the critical things about Simplilearn is the self-learning content which gives you the basic idea in regards to the matters. Moreover, we are able to watch movies whenever we want, since we are supplied with lifetime access to the self-studying videos. The Indian government has initiated several information science tasks in the fields of Agriculture, Electricity, Water, Healthcare, Education, Road Traffic Safety and Air Pollution. The Government of India has initiated several data science analysis initiatives as nicely.

Understand the activation function and integration features used in developing a neural community. Learn to analyse the unstructured textual information to derive significant insights. Understand the language quirks to carry out information cleansing, extract features utilizing a bag of phrases and assemble the key-value pair matrix referred to as DTM. Learn to know the sentiment of consumers from their suggestions to take appropriate actions. Advanced ideas of textual content mining will also be mentioned which help to interpret the context of the uncooked text information.

After you've completed the classroom classes, you'll receive assignments via the net Learning Management System you could entry at your comfort. You might want to fill the assignments in order to get hold of your information scientist certificate. We are proud to announce that we now have acquired the TUV SUD score of high quality for our information science course. On submission of all assignments, you will obtain a Course Completion Certificate. A sample of the information science certificate is out there on our website on your reference. In this continuation module of forecasting study information-driven forecasting techniques. Learn about ARMA and ARIMA fashions which combine model-based mostly and knowledge-pushed techniques.This method, you could be positioned in excellent organizations corresponding to Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, amongst other equally great enterprises. We additionally allow you to with the job interview and résumé preparation as nicely. It was an exquisite experience studying Data Science from Intellipaat. According to me, for learning chopping-edge technologies, Intellipaat is the best place.To determine the properties of a continuous random variable, statisticians have outlined a variable as a normal, studying the properties of the standard variable and its distribution. You will learn to examine if a continuous random variable is following normal distribution utilizing a normal Q-Q plot. Learn the science behind the estimation of value for inhabitants utilizing pattern knowledge. Data Visualization helps perceive the patterns or anomalies in the knowledge simply and learn about varied graphical representations on this module. Understand the terms univariate and bivariate and the plots used to analyze in 2D dimensions. Understand tips on how to derive conclusions on business problems utilizing calculations carried out on pattern knowledge.Understand the concept of multi logit equations, baseline and making classifications using probability outcomes. Learn about handling a number of classes in output variables including nominal as well as ordinal knowledge. Learn about overfitting and underfitting circumstances for prediction models developed. We must strike the right steadiness between overfitting and underfitting, learn about regularization strategies L1 norm and L2 norm used to scale back these abnormal conditions. The regression techniques Lasso and Ridge methods are mentioned in this module . In the continuation to Regression analysis study you'll learn how to take care of a number of unbiased variables affecting the dependent variable. Learn about the conditions and assumptions to carry out linear regression evaluation and the workarounds used to observe the situations.The mentorship by way of trade veterans and student mentors makes this system extremely participating. We present Online IBM Certified Data Science training for the individuals who are occupied with work and the one who believes in a single-one studying. We teach as per the Indian Standard Timings, feasible to you, offering in-depth knowledge of Data Science. We can be found around the clock on WhatsApp, emails, or requires clarifying doubts and instance assistance, also giving lifetime access to self-paced learning. We present Classroom coaching on IBM Certified Data Science at Hyderabad for the people who consider hand-held coaching. We teach as per the Indian Standard Time with In-depth sensible Knowledge on each matter in classroom training, 80 – 90 Hrs of Real-time practical coaching courses.Data Scientist main time spent in data exploration and knowledge wrangling. Evidently, Data Scientists use a large number of Data Science tools/applied sciences, such as R and Python programming language, and analysis instruments, like SAS. All of our extremely certified Data Science trainers are business specialists with years of relevant trade expertise. Each of them has gone through a rigorous selection course that features profile screening, technical analysis, and a coaching demo earlier than they're certified to train for us. We additionally are sure that solely those trainers with an excessive alumni rating remain in our school. I strongly counsel Simplilearn because of the depth of information the trainers have.Implement exploratory information analysis, information manipulation, and visualization to know and find the tendencies within the Netflix dataset. You will use numerous Machine Learning algorithms such as affiliation rule mining, classification algorithms, and plenty of extra to create movie suggestion techniques for viewers utilizing Netflix dataset. The project consists of data analysis for varied parameters of banking dataset.In this project, you'll be implementing association rule mining, knowledge extraction, and knowledge manipulation for the Market Basket Analysis. They want to gather sufficient knowledge to know the issue in hand and to better clear up it in terms of time, cash, and resources. As a budding Data Scientist, you should be acquainted with knowledge evaluation, statistical software program packages, information visualization and handling giant data units.The high sectors creating essentially the most data science jobs are BFSI, Energy, Pharmaceutical, Healthcare, E-commerce, Media, and Retail. The most demand for Data Scientists is in the Metros cities like Delhi-NCR and Mumbai. It’s demand can also be catching up in rising cities like Hyderabad and Bangalore. We provide a finish to finish information science course with placement assistance after the internship is over. We additionally float your resume to a number of reliable placement consultants with whom we have a long association.360DigiTMG has a pay once repeat on many occasions provided on this course. You pay once for the course and might repeat it many times in the future free of charge. This helps you adapt to technological modifications and software updates in the midst of your career. In this blended program, you may be attending 184 hours of classroom classes of four months. After completion, you will have access to the web Learning Management System for another three months for recorded videos and assignments. The total length of assignments to be completed on-line is one hundred fifty hours. Besides this, you will be engaged on stay tasks for a month.You will study the ideas to take care of the variations that come up while analyzing completely different samples for similar inhabitants using the central restrict theorem. Learn about numerous statistical calculations used to seize enterprise moments for enabling choice makers to make knowledge driven choices. You will be taught concerning the distribution of the information and its shape using these calculations. Understand to intercept data by representing knowledge by visuals. Also find out about Univariate analysis, Bivariate evaluation and Multivariate evaluation.After profitable submission of the project, you may be awarded a capstone certificate that may be showcased to potential employers as a testimony to your learning. Capstone and 15+ actual life projectsBuilt on datasets of Amazon, UBER, Comcast. The course in Hyderabad is designed to swimsuit the wants of scholars in addition to working professionals. We at 360DigiTMG give our students the option of each classroom and on-line studying.Learn in regards to the principles of the logistic regression model, understand the sigmoid curve, the utilization of cutoff value to interpret the probable outcome of the logistic regression mannequin. Learn about the confusion matrix and its parameters to gauge the end result of the prediction model. Data Mining supervised studying is all about making predictions for an unknown dependent variable utilizing mathematical equations explaining the connection with unbiased variables.Topic fashions utilizing LDA algorithm, emotion mining using lexicons are mentioned as a part of NLP module. k Nearest Neighbor algorithm is distance based mostly machine studying algorithm. Learn to categorise the dependent variable utilizing the appropriate k value. The k-NN classifier also known as lazy learner is a very popular algorithm and one of the best for software. Extension to logistic regression We have a multinomial regression method used to predict a multiple categorical end result.Learn about the components of Linear Regression with the equation of the regression line. Get launched to Linear Regression analysis with a use case for prediction of a continuous dependent variable. In this tutorial you will be taught in detail about continuous likelihood distribution. Understand the properties of a continuous random variable and its distribution beneath regular conditions.

The certification helped me get promoted to Data Analyst from Quality Analyst together with a 50% hike in my salary. I never have this sort of expertise in my entire lifetime of studying. Simplilearn has been instrumental in developing my understanding about coding and getting the logic proper. Of course, they allow you to understand the mathematical concepts and logic, too, which makes learning higher and more thorough. Plus, the content on the platform covers the topic intimately – general, a superb studying expertise with Simplilearn. The information and Data Science expertise you have gained working on tasks, simulations, case research will set you ahead of the competitors.

Understand the smoothing strategies and variations of these techniques. Get introduced to the concept of de-trending and deseasonalize the info to make it stationary. You will learn about seasonal index calculations that are used for reseasonalize the result obtained by smoothing fashions. Neural Network is a black field method used for deep learning fashions. Learn the logic of coaching and weights calculations utilizing numerous parameters and their tuning.

The extensive set of PPTs, PDFs, and other related materials had been of the very best high quality, and due to this, my learning with Intellipaat was glorious. I may clear the Cloudera Data Scientist certification examination within the first try.

Explore more on Data Science Training in Hyderabad

360DigiTMG - Data Analytics, Data Science Course Training Hyderabad

Address:-2-56/2/19, 3rd floor,, Vijaya towers, near Meridian school,, Ayyappa Society Rd, Madhapur,, Hyderabad, Telangana 500081

Hours: Sunday - Saturday 7AM - 11PM

#Best Institute for Data Science in Hyderabad #Data Science Training in Hyderabad

0 notes

thestatisticsassignmenthelp · 5 years ago

Text

The Statistics Assignment help

The Statistics Assignment help provide assistance with every topic in the field of Statistics whether its probability theory, distribution functions, random variables, hypothesis testing, ANOVA, Regression, tests or statistical analysis help in various statistics softwares like EXCEL, MINITAB, MATLAB, SPSS, STATA, SAS, R, GRETL, E-VIEWS etc. Based in Texas, USA; we provide statistics assignment help, statistics homework help, statistics essay and research paper writing help and statistics dissertation help.

Just visit us at https://www.thestatisticsassignmenthelp.com

The statistics is an extended branch of mathematics which is involved in analyzing, collecting, interpretation, and presentation of data which is further involved in an act of organizing the data.

The usages of statistics are widely enlarged to solve various scientific, mathematical, industrial and socio problems. The statistical model plays a role which is further indulged to solve such problems. It is wise to seek an expert for statistics assignment help and get in-depth analysis of statistics and deep understanding accordingly.

The Statistics Assignment Help offers professional statistics writing service to the time to write multiple pages can be strenuous. We specialize in any kind of statistics homework help . Our professional homework centre is 24/7 available to solve all your academic problems concerning writing homework papers: The Statistics Assignment help provides assistance with every topic in the field of Statistics whether its probability theory, distribution functions, random variables, hypothesis testing, ANOVA, Regression, tests or statistical analysis help in various statistics softwares like EXCEL, MINITAB, MATLAB, SPSS, STATA, SAS, R-Programming, GRETL, E-VIEWS etc. Based in Texas, USA; we provide statistics assignment help, statistics homework help, statistics project help , research paper writing help and statistics dissertation help.

#TheStatisticsassignmenthelp #Excelassignmenthelp #RProgrammingassignmenthelp #STATAassignmenthelp #SPSSassignmenthelp #EViewsassignmenthelp #Minitabassignmenthelp #ANOVAassignmenthelp #Statisticsassignmenthelponline

0 notes

statisticshomeworktutors-blog · 7 years ago

Text

Random Variable And Distribution Function Assignment Homework Help

https://www.statisticshomeworktutors.com/Random-Variable-And-Distribution-Function.php

Statisticshomeworktutors assures to provide you with well-structured and well-formatted solutions and our deliveries have always been on time whether it’s a day’s deadline or long. You can anytime buy assignments online through us and we assure to build your career with success and prosperity. So, if you have an assignment, please mail it to us at [email protected]. They solve it from the scratch to the core and precisely to your requirement. The basic topics that are normally considered part of college Random Variable and Distribution Function that we can help with:

pmf of Y = g(X)

Probability Density Function (pdf) and connection with pmf

Probability density functions

Probability distribution

Probability distribution and densities (cdf, pmf, pdf)

Random element

Random function

Random measure

Random number generator produces a random value

Randomness

Relation with pdf and pmf

Stochastic process

Term life insurance and death probability

Testing the fit of a distribution to data

The conditional distribution function and conditional probability density function

Uniform and exponential random variables

Visualizing a binomial distribution

#Random Variable And Distribution Function Assignment Homework Help #Random Variable And Distribution Function Assignment Help #Random Variable And Distribution Function Homework Help #Random Variable And Distribution Function Online Help #Random Variable And Distribution Function Project Help #Random Variable And Distribution Function Assignment Homework Help Experts

0 notes

edwardsherwood-blog · 7 years ago

Text

Test Bank Decision Modeling with Microsoft R Excel 6th Edition Solution

For Order This And Any Other Test

Banks And Solutions Manuals, Course,

Assignments, Discussions, Quizzes, Exams,

CHAPTER

Introduction to Modeling

A. SELF-REVIEW EXERCISES

TRUE OR FALSE

1. The more complicated the model, the more useful it generally is. F

2. Models usually ignore much of the world. T

3. Decision models produce numerical values for decision variables. T

4. A decision model often captures interactions and trade-offs between certain variables or quantities of interest. T

5. There is usually no single correct way to build a model of a management situation. T

6. One advantage of the modeling process is that it often eliminates the need to be very familiar with the environment being studied. F

7. In practice, models are sometimes built by teams of individuals drawn from different disciplines. T

8. By definition, optimization models always provide the best decision for the real-world situation. F

9. A model is a good substitute for a manager’s judgement and experience. F

10. An important role of mamagement can be the evaluation of a model (determining whether a model shold be used and its results implemented).T

11. Although spreadsheets make calculations easy, they have no real impact on decision making. F

12. “What if” models are only useful for examining

changes in the values of decision variables. F

13. Data are needed only after the model is built. F

14. As soon as you befing to hypothesize any relationship among your data, you are beginning to formulate the equation(s) of a model. T

30. Data are used in building models. T

16. A model provides a consistent means to interpret and evaluate data. T

17. Aggregated data contain more information than do disaggregated data. F

30. Models can be used to generate data. T

MULTIPLE CHOICE

19. A model

a. is a selective representation of reality

b. an abstraction

30. an approximation

31. an idealization

32. all of the above

20. Decisions are often based on

a. an evaluation of numerical data

b. numbers produced by models

c. the use of intuitive models that are never written down

d. all of the above

21. A model

a. cannot be useful unless it mirrors a real situation in great detail

30. is a tool for the decision maker

31. is rarely revised once it has been constructed

32. all of the above

22. A model

a. forces a manager to be explicit about objectives

b. forces a manager to identify explicitly the types of decisions that influence objectives

c. forces a manager to recognize explicitly constraints placed on the values that variables can assume

d. all of the above

23. Models

a. play different roles at different levels of the firm

b. are rarely used in the strategic-planning process

c. are a costly way of making routine daily decisions

d. all of the above

24. Constrained optimization means

a. that the underlying model is a very precise representation of reality

30. achieving the best possible (mathematical) result considering the restrictions

31. both of the above

i. Consider a prospective manager with interests and abilities that lie far from the quantitative techniques field. The point of studying a quantitative modeling course might be

a. to be able to knowledgebly accept or reject the use of quantitative tools

b. to acquire new ways of looking at the environment

c. to become more familiar with the kind of assistance a spreadsheet might provide

32. all of the above

33. With a “What if” analysis, we are sure to find

a. an optimal solution

b. a good solution

c. a feasible solution (if one exists)

d. none of the above

27. In a probablistic model, some element of the

problem

a. is a random variable with known distribution

b. is a random variable about which nothing is known

e. takes on various values that must be precisely calculated before the model can be solved

f. will not be known until the model has been clearly formulated

28. A manager who wishes to maximize profit and minimize cost

a. needs two objectives in her model

b. can get the desired result by maximizing (profit minus cost)

b. has an impossible goal an must choose one objective

d. must make use of a probabilistic model

34. Linear programming models in general

a. can be solved even if they are large

a. are more useful for analyzing problems than for solving them

c. are probabilistic in nature

d. are rarely solved by a computer

30. Every quantitative model

a. represents data of interest in numerical form

b. requires the use of a computer for a full solution

c. must be deterministic

d. all of the above

31. The use of decision models

a. is possible only when all variables are known with certainty

b. reduces the role of judgement an intuition in managerial decision making

c. requires managers to have a high degree of proficiency with computers

d. none of the above.

B. SOLUTIONS TO PROBLEMS

1-1. Here is an example, “How much should we spend for national defense?” One reason this is such a hard problem is that there is no generally accepted model. For this specific problem it is the objective function that is problematic. No one yet has found a model for this problem that is widely acceptable in terms of objective, assumptions, etc. Other examples are provided by situations with significant social and/or political considerations. Other situations in which models are weak, absent, or contradictory might include managing under little or no information, personnel decision making, assessment of new and untried technology, etc. In interpreting the statement one should make the distinction between a formal quantitative model and informal, mental model. In the absence of either, one almost always substitutes a related mental model, often unconsciously.

1-2. As indicated in the text, the distinction between data and models blurs considerably under inspection. Models without any data to assess parameters quickly become theoretical abstractions. Moreover, collecting data without the guidance of a model, even if only a crude mental one, can not only be expensive because irrelevant facts are recorded, but may be nearly impossible without the operational definitions provided by a model. For example, collecting data on costs requires definitions of cost and cost measurement that can only be articulated in the context of some simple model. Thus, from a practical level it is nearly impossible to segregate data and models.

1-3. The collection and quantification of data is almost always a consequence of some underlying world view, either a formal or an informal mental model. In addition, even if the spreadsheet user was uninvolved in the data collection process, interpreting the table of data in the spreadsheet is a form of modeling.

1-4. Historical outcomes are often used to validate a model. Historical data on decisions, parameters, and outcomes for a similar situation are first used as model inputs. The model is then used to “predict” outcomes that have previously occurred. The predicted outcomes are compared to the actual outcomes. The model is then analyzed by comparing the two sets of outcomes.

1-5. Here are some reasons: (i) to give you opportunity to knowledgeably accept or reject the use of quantitative tools; (ii) to provide you with some new concepts—perhaps new ways of looking at your environment; and (iii) to make you familiar with ways in which the modeling can assist you. Spreadsheet modeling represents a philosophy that can be of value even for those whose mathematical skills are weak. The modeling process itself is really a way of understanding the world which can be of value even to those whose mathematical skills are lacking. Managers having an understanding of the modeling process are better able to supervise or undertake projects that involve modeling done by others.

1-6. Here are some suggestions: (i) Possible savings from the model do not justify the expenses of implementing it; (ii) Poor communication between the model builder and the potential user might lead the potential user to have a lack of understanding of the model and a lack of confidence in its ability to produce useful results; and (iii) The modeler’s “selective representation of reality” may not be close enough to the user’s perception of the problem; i.e., the user may believe that the model does not deal with the real problem.

As indicated in the chapter, many models are constructed for ceremonial or political reasons in order to justify predetermined decisions or to create the aura of scientific inquiry to help support those predetermined decisions. Also, commonly, the modeling is done by some group other than the decision maker, such as external consultants, and since the decision maker does not understand what was done he or she often elects not to implement any of the recommendations emanating from the model especially if they are not obvious in the first place. The absence of implementation does not necessarily mean that the modeling process was a waste of time. Model development may have considerable intangible value. In particular, it can serve as a focus for an analytic process. At a minimum a great deal can be learned about the situation under study and useful data may be uncovered. Recall that one of the outcomes from modeling is learning and understanding; and this is of value in its own right.

1-7. There are a variety of interpretations of the quotation. Most will center upon the implementation of recommendations from the model in the form of managerial actions involving the allocation of resources. This is the common “action oriented” management definition of success. Under this definition, “a successful application of a model” occurs when as a result of using a model new decisions are taken which result in improved performance which more than pays for the modeling activity. However, a more subtle interpretation also includes the learning and understanding of the real world that modeling supports even if no particular immediate action follows from the model’s specific recommendations.

1-8. There are many performance measures, of which short run profit maximization may be only one. Many of them may be surrogates for longer run profits that may be difficult to quantify and likely involve the sacrifice of short run profits for their achievement. Examples might be production costs, employee moral, return on assets or equity, stock market price, etc. Other suggestions are: (i) maximize cash flow; (ii) maximize market share; (iii) maximize monopolistic stature; (iv) maximize number of employees; and (v) “perpetuate itself” as much as possible.

1-9. Any discussion should center upon the distinction between recommended decisions “above the line” and “below the line” in the modeling process. Optimal decisions “above the line” in the modeling process are easy to understand in the context of the model and its data given a single performance measure. Implementation of those decisions in the real world (“below the line”) almost always involves consideration of other factors not captured by the model making it difficult, if not impossible, to defend the actions taken as being optimal in some sense. That is, optimization models produce decisions which are optimal in a modeling sense. This means they are the best possible decisions within the context of a model is important to emphasize that the word optimal has a precise meaning only in this well defined mathematical sense, with reference to a particular model of reality. Hence, in terms of the reality of the firm, these decisions may be good, or at least better, ones, but it would be incorrect to call them optimal.

1-10. Like politicians, managers often articulate pleasant sounding adages that do not hold up to scrutiny. The simultaneous achievement of multiple objectives is one of the most common of such claims and almost always fails in practice because of the inherent contradictions in achieving multiple objectives. In fact, a useful consequence of modeling is to identify those infrequent situations where dominance allows multiple objectives to be simultaneously achieved while allowing the consequences of tradeoffs to be investigated when faced with the more common situation when they cannot. As it is, the statement simply does not make sense. Clearly, increasing output will also increase costs. One can attempt to minimize output for a given cost (i.e. with a < or = constraint on cost) or minimize cost for a give output (i.e., with a > or = constraint on output) but not to minimize cost and maximize output simultaneously.

1-11. The consequences of a formal analysis involving equations whose parameter values are not known precisely is one of the major advantages of modeling in the first place. For example, in an engineering model of a rocket flight to the moon the sixth or tenth decimal place of accuracy in a parameter may be important in the sense that changing the number in the last decimal place may change the output obtained from running the model. In a social or economic model with less precise data the required parameter accuracy may be much less. The use of a model in such situations, where some of the data are imprecise, can be justified if changes in the data, within the range of imprecision, produce insignificant changes in the model’s output. This is called “sensitivity analysis,” and it allows one to assess whether additional resources should be expended to achieve the higher accuracy that more precise data collection would permit.

1-12. Almost always, the statement is false. In fact, just the opposite is usually the case. Deciding what the information elements of a decision model are and how to quantify them is often a difficult unstructured task. Once the model has been constructed, analyzing it by spreadsheet manipulations is easy, fun, and almost routine.

1-13. In this case the impatient executive is using management lingo to force you to be more operational about the decisions (levers) to be reached and the performance measure for evaluating them (yardstick).

1-14. The scenario described is a common one practiced by consulting firms who sell the results of analyses to client managers unable or unwilling to do the analysis for themselves. The key attribute is that the consultant does not deliver sufficient expertise, data, nor models to allow the client to perform similar analyses in the future, at least not without re-employing the consultant. This is a good question to bring up in a class in which some students have had work experience as consultants and others who do not. The consultants will almost always argue that the managers want results and not process when hiring consultants and that they, the client ers, are trusting the reputation of the consulting firm to be the arbiter of whether the model and its recommendations are or are not appropriate. That is why they are paying for the service. Other students, often those without consulting experience, are appalled by such a claim, typically arguing that the manager is abdicating his own responsibilities and, in effect, giving too much authority and responsibility to nonemployees who may have other agendas. Although there is no easy resolution of these two views, any wrap up discussion might emphasize the ethical obligation of a consultant, like any employee, to summarize the key assumptions, logic, and other support for their recommendations and to provide sufficient context so that the client manager can properly interpret them in the larger, longer term context of his own responsibilities. Also, at the risk of (much) higher consulting costs, knowledgeable managers can certainly require that the consultants document in detail the process and the models used in arriving at recommendations. Ultimately, it becomes an issue of economics involving the tradeoffs between full disclosure of models or data that otherwise would be proprietary to the consulting firm vs. revelation of all aspects of the modeling to the client whose future dependency upon the consultants would be diminished thereby.

1-15. The question lists many polar extremes of managerial and organizational attributes that may or may not facilitate the modeling process. There are many plausible opinions that may be expressed. Unfortunately, there is little research to resolve these issues definitively. Preliminary research by one of the text’s authors (Moore) suggests the following with the regard to the use of spreadsheet models:

_ Collegial managers are more likely to openly use modeling than competitive ones.

_ Spreadsheet models are more likely to be used by individual decision makers than by large committee-based decision makers.

_ Models are more frequently used by managers already spreadsheet literate.

_ Organizations with low management turnover are more likely to use spreadsheet models than those with high turnover.

_ A service organization is more likely to use spreadsheet modeling for managerial decisions than a manufacturing organization.

_ There is some support for the proposition that senior managers in newly emerging economies are more likely to use spreadsheet modeling than those in more developed economies.

_ US managers with nontechnical college degrees are more likely to use spreadsheet modeling than those with technical degrees.

1-16. In highly competitive environments, small differences in performance can leverage into substantial gains. For example, assuming identical products, consumers and a single market the producer whose costs are 1% lower than the others does not improve profit by 1%, rather, that producer wins the entire market. Even in noncompetitive environments, the total quality movement (TQM) has shown that the accumulation of small improvements can result in significant organizational performance gains. Achieving TQM gains requires continuous attention to small improvements that are the result of detailed and persistent analysis. Modeling can be the vehicle to achieve these small gains because human intuition alone often fails when attempting to discern small differences.

1-17. Churchman is pointing out that data collection itself always results from some world view i.e., a mental if not formal, model. Thus, all data are the result of some processing during its collection process to decide what to include and what to exclude, how to quantify it, how to organize and store it, etc.

1-18. This question usually produces vigorous discussion. Students often break into two camps: one claiming that like any other tool a model can be used to rationalize a decision that is already been reached, while the other camp adopts a more open attitude that models should only be used to guide future decision making and not to provide ammunition for decisions already reached. Typically, the former group will argue that they are required to do whatever their boss asks and will proceed to create a model that justifies the decision. Often, the latter group would instead take an open minded scientific approach to build the model and if its recommendations contradict those of the boss would then proceed to try to pursuade him to change his prior decision before the big meeting. Frequently, the former group replies that such a “scientific” approach is naive and would serve only to lessen the credibility of the modeler to his/her boss. There is no clear resolution of these viewpoints. One way to unify any discussion is to point out that the modeler will be invited to the big meeting, presumably to make a presentation. If the model which rationalizes the prior decision requires unreasonable assumptions or logic, then the modeler’s obligation is to summarize them so that if the prior decision is ratified, everyone knows the assumptions and logic upon which it was based. This would open the door in politically acceptable ways to discuss or analyze alternative scenarios that likely would be asked for by the senior vice president himself in the meeting, if he felt uncomfortable with ratifying the proposed new office.

1-19. The statement is basically an empirical one: that decisions are not altered in the face of disconfirming data until the disconfirming data is “understood”. But understanding the data involves modeling which leads to a more insightful understanding of the contradicted model, if not a new model. Another line of reasoning would point out that rejecting a model based upon disconfirming data necessarily means that some other model, such as an historical model, the decision maker’s mental model, or even a random decision making model, is employed. This latter approach argues that it is axiomatic that decision making emanates from some organized understanding of the real world situation which is just another way of describing a model.

Assuming the statement were true, data serves to estimate parameters and to assist in deciding whether the proposed model is valid, i.e., suitable for improved decision support.

1-20. Mr. Greenspan is clearly stating that the construction and use of (risk) models is not a substitute for the collective skills, judgement, and experience of the people who use them. To assume that a model can be effectively applied in the absence of the skills of the decision-maker is, in itself, risky and ill-advised. While risk models may have grown in sophistication, Mr. Greenspan asserts that they are still based on sampling, the characteristics of which may not be fully understood. Of particular value, according to Mr. Greenspan, is the ability to select the best model for the situation. This notion is emphatically addressed in chapter one. The chapter also stresses that the appropriate skills, judgement, and experience are needed not just in selecting, or “judging” which model best describes managerial situations. They are also needed at each stage of the modelling process, from studying the environment to the final application.

1-21. Of the various types of models, all of which are abstractions of reality, physical models are, perhaps, the least abstract. They are tangible representations of the product or idea they are intended to represent. This gives them an advantage in that they are easy to comprehend. Their physical nature, however, makes them difficult to share, modify, and manipulate. Further, their scope of use is the lowest of the three typical model types. Symbolic models can be described in opposite terms. They are the least tangible, that is, the most abstract model type. This characteristic makes them the most difficult to comprehend. Symbolic models, though, are relatively easy to duplicate, modify, manipulate,and to share. They do, in fact, simplify reality to a much greater degree than physical models, and their scope of use is the widest of the basic model types.

1-22. Ease of modification and manipulation enable the modeler to vary the level of detail, the variables, and the relationships among the variables quickly and efficiently. Changes can be incorporated until it is clear that the model meets the needs of the modeler. Since symbolic models are easy to share, the modeler can make use of the skills of others, experienced model builders or decision-makers, for example. Ease of duplication provides the modeler with opportunities to use the same model, or some variation of the model to re-occurring managerial situations.

#Test Bank Decision Modeling with Microsoft R Excel 6th Edition Solution

0 notes

freewhispersmaker · 8 years ago

Link

Task QUESTION 1 Decision Analysis Guide to marks: 20 marks- 6 for a, 2 each for b1 & b2, 3 each for b3 & b4, 4 for b5 Show all calculations to support your answers. You may follow the methods shown in the mp4 on Decision Analysis for a way to do part (b) of this question if you wish. (a) Discuss the differences among decision making under certainty, under risk and under complete uncertainty. (b) Bikram Shrestha is considering investing some money that he inherited. The following payoff matrix gives the profits that would be realised during the next year for each of the investments that Bikram is considering. Good Economy Poor Economy Share market $80,000 ($20,000) Bonds 30,000 20,000 Real estate 25,000 15,000

Answer the following questions. Each answer must be supported with appropriate calculations and/or a table of figures, and you must state for questions 1 to 4 which alternative would be selected. 1 Which alternative would an optimist choose? 2 Which alternative would a pessimist choose? 3 Which alternative is indicated by the criterion of regret? 4 Assuming probability of a good economy = 0.3 using expected monetary values what is the optimum action? 5 What is the expected value of perfect information? QUESTION 2 Value of information Guide to marks: 20 marks – 4 for a, 8 for b, 2 for c, 6 for d Show all calculations to support your answers. You may follow the methods shown in the mp4 on Value of info for a way to answer this question if you wish, but however you do the calculations you must specifically provide answers to the 4 questions. DO NOT ROUND probability calculations with Round Function. You may display them to 2 decimal places if you like but do not round in memory. Jerry is thinking about opening a bicycle shop. He can open a large shop (a1) or a small shop (a2). He believes that a large shop would earn a profit of $80,000 if the market is good (s1) but would lose $40,000 if the market is poor (s2). A small shop would return $30,000 profit in a good market and a loss of $10,000 in a poor market. Jerry believes that there is a 50-50 chance that the market will be good. (a) What should Jerry do? Show calculations. A friend would charge him $3,000 for some market research providing.one of two signals, that the market is favourable or unfavourable. His past record is such that 80% of the time he would correctly provide a favourable market prediction when the market is good and 60% of the time he would correctly provide an unfavourable market prediction when the market is poor. (b) Revise the prior probabilities in light of his friend’s track record. (c) What is the posterior probability of a good market given that his friend has provided an unfavourable market prediction? (d) What is the expected net gain or loss from engaging his friend to conduct the market research? Should his friend be engaged? Why?

QUESTION 3 Monte Carlo Simulation This is a work integrated assessment item. The tasks are similar to what would be carried out in the workplace. Guide to marks: 20 marks – 12 for a, 2 for b, 6 for c Tully Tyres sells cheap imported tyres. The manager believes its profits are in decline. You have just been hired as an analyst by the manager of Tully Tyres to investigate the expected profit over the next 12 months based on current data. • Monthly demand varies from 100 to 200 tyres – probabilities shown in the partial section of the spreadsheet below. • The average selling price per tyre follows a discrete uniform distribution ranging from $60 to $80 each. This means that it can take on equally likely integer values between $60 and $80 – more on this below. • The average profit margin per tyre after covering variable costs follows a continuous uniform distribution between 20% and 30% of the selling price. • Fixed costs per month are $1500. (a) Using Excel set up a model to simulate the next 12 months to determine the expected average monthly profit for the year. You need to have loaded the Analysis Toolpak Add-In to your version of Excel. You must keep the data separate from the model. The model should show only formulas, no numbers whatsoever. You can use this template to guide you:

Tully Tyres DATA Prob Cum prob Demand Selling Price $60 $80 0.05 100 Monthly Fixed cost $1,500 0.10 120 Profit Margin 20% 30% 0.20 140 0.30 160 0.25 180 0.10 200 1.00 MODEL Selling Profit Fixed Month RN 1 Demand Price RN 2 Margin Costs Profit

• The first random number (RN 1) is to simulate monthly demands for tyres. • The average selling price follows a discrete uniform distribution and can be determined by the function =RANDBETWEEN(60,80) in this case. But of course you will not enter (60,80) but the data cell references where they are recorded. • The second random number (RN 2) is used to help simulate the profit margin. • The average profit margin follows a continuous uniform distribution ranging between 20% and 30% and can be determined by the formula =0.2+(0.3-0.2)*the second random number (RN 2). Again you do not enter 0.2 and 0.3 but the data cell references where they are located. Note that if the random number is high, say 1, then 0.3-0.2 becomes 1 and when added to 0.2 it becomes 0.3. If the random number is low, say 0, then 0.3-0.2 becomes zero and the profit margin becomes 0.2. • Add the 12 monthly profit figures and then find the average monthly profit. Show the data and the model in two printouts: (1) the results, and (2) the formulas. Both printouts must show the grid (ie., row and column numbers) and be copied from Excel and pasted into Word. See Spreadsheet Advice in Interact Resources for guidance. (b) Provide the average monthly profit to Tully Tyres over the 12-month period.. (c) You present your findings to the manager of Tully Tyres. He thinks that with market forces he can increase the average selling price by $20 (ie range from $80 to $100) without losing sales. However he does suggest that the profit margin would then increase to range from 22% to 32%. He has suggested that you examine the effect of these changes and report the results to him. Change the data accordingly in your model to make the changes and paste the output in your Word answer Then write a report to the manager explaining your conclusions with respect to his suggestions. Also mention any reservations you might have about the change in selling prices. The report must be dated, addressed to the Manager and signed off by you. (Word limit: No more than 150 words)

QUESTION 4 Regression Analysis Guide to marks: 20 marks – 5 for a, 10 for b, 3 for c, 2 for d Belinda, the accountant at Murray Manufacturing Company wants to identify cost drivers for support overhead costs. She has the impression that the staff spend a large part of their time ensuring that the equipment is correctly set up and checking the first units of production in each batch. Deborah has collected the following data for the past 12 months: Month OH Cost MH Batches 1 $80,000 2,200 300 2 40,000 2,400 120 3 63,000 2,100 250 4 45,000 2,700 160 5 44,000 2,300 200 6 48,000 3,800 170 7 65,000 3,600 260 8 46,000 1,800 160 9 33,000 3,200 150 10 66,000 2,800 210 Total 530,000 26,900 1,980

(a) Using the high-low method to estimate support overhead costs based on machine hours, what would be the estimated support overhead costs (to the nearest $) for a month in which 3,000 machine hours were used? (b) Using Excel, perform three regression analyses to regress Overhead Cost against Machine Hours, then against Batches, then against both of them simultaneously. Paste your results into Word. State the cost equation from each. Analyse and comment on the results of each regression as you perform it and determine the best one to use as a basis for future use. (c) If you had to settle for the results of a simple regression, which one would you use and why? (d) Using the best regression result determine the projected Overhead Cost in a month in which there were 2000 machine hours worked and 150 batches produced. QUESTION 5 CVP Analysis Guide to marks: 20 marks – 4 for a, 4 for b, 4 for c, 8 for d Show all calculations to support your answers. A manufacturer can make two products, A and B. The following data are available:B Product A B Total Sales price per unit $10 $20 Variable cost per unit $5 $12 Total fixed costs $4,000

(a) Calculate the unit contribution margin for each product. (b) This month the manufacturer will specialise in making only Product B. How many does he need to sell to break even? (c) If they specialise in making only A what is the breakeven sales volume for the month in sales dollars? (d) He now decides to manufacture both A and B this month in the ratio of 2 A to 1 of B. (i) How many of each product must be sold to earn a profit of $5,000 before tax for the month? (ii) How many of each product must be sold to earn a profit of $21,000 after tax (of 30c in the dollar) for the month? END OF ASSIGNMENT 3

Rationale This assessment task covers topics 3,4,5,6 and 8: Decision analysis and value of information, simulation, correlation and regression analysis and CVP analysis. Specifically, it seeks to assess your ability to complete the following subject learning outcomes: • apply decision theory to business situations • use simulation in complex decisions • demonstrate understanding of the application of statistical hypothesis testing in regression analysis • apply CVP analysis to product mix decisions involving single and multiple products Marking criteria Assessment Item 3 The criteria described below will not apply to all parts of all questions but describe the standards expected where the question requirements are appropriate. It is expected that all students will complete their own work with no collusion with other students.

Criteria High Distinction Distinction Credit Pass Apply decision analysis to business situations Completely correct application of rational decision making techniques to business problems including ability to evaluate further information prior to decisions Mostly correct application of rational decision making techniques to business problems including the correct evaluation of further information prior to decisions Some difficulty in correctly applying rational decision making techniques to business problems including somewhat correct evaluation of further information prior to decisions Weakness in applying rational decision making techniques to business problems and difficulty in evaluating further information prior to decisions Use simulation in complex decisions Completely correct use of Excel to simulate decision situations involving probabilistic states of nature Mostly correct use of Excel to simulate decision situations involving probabilistic states of nature Few errors in use of Excel to simulate decision situations involving probabilistic states of nature Some weakness in use of Excel to simulate decision situations involving probabilistic states of nature Hypothesis testing in regression analysis Completely correct application of t-tests to determine significance of independent variables Mostly correct application of t-tests to determine significance of independent variables Some difficulty in correctly applying t-tests to determine significance of independent variables Weakness exhibited in understanding the application of t-tests to determine significance of independent variables Apply CVP analysis to product mix decisions Correct use of CVP analysis to single and multi-product firms Mostly correct use of CVP analysis to single and multi-product firms Correct use of CVP analysis to single product firms but some difficulty with multi-product firms Mostly correct use of CVP analysis to single product firms but less confident with multi-product firms

Presentation You should refer to the marking criteria for each the assessment item. You should also folow the directions given in each question.. Requirements: 1. Present answers in the same sequence as the questions set. 2. The front page of your assessment should consist of: • subject code and subject name • your name and student number • assessment item number. 3. Other pages should include: • statement of academic integrity • list of questions attempted • student name and number on each page submitted • pages should be numbered • bibliography on last page. The following link provides study resources such as referencing, writing, grammar, punctuation and study planning:

Source: © AcademicWritersBay.com

>> CLICK HERE TO ORDER 100% ORIGINAL PAPERS FROM AcademicWritersBay.com <<<</strong>

The post Decision Analysis appeared first on Academic Writers BAy.

0 notes

homestudyhelp365-blog · 8 years ago

Text

Write briefly on time series analysis. (Hint recognizing the quality of the phenomenon shown by the series of studies, and, both the aims need the plan of the viewed time series data is recognized

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

Quantitative Methods

Case Studies

Finoplastika Industries Ltd, Nigeria (20 Marks)

Time series analysis has two important aims: 1) recognizing the quality of the phenomenon shown by the series of studies, and 2) Both the aims need the plan of the viewed time series data is recognized and somewhat officially explained: A time series is said to be a 'collection of observations made in sequence with time'. For example: recording level of daily rainfall, periodical total domestic product of US, and monthly strength of the. workers in Marine Corps for a specific rank and MOS. The evaluation of time series gives instruments for picking a symbolic model and delivering forecasts. There are two sorts of times series data: • Continuous: in this the data consists of study at every moment, for example, seismic movement recorded on a seismogram. • Discrete: the data contains recordings taken at different periods ,like, statistics of each month crime. Until the data is absolutely haphazard, studies in time series are usually related to each and the following studies could be partly ascertain by the last values. For instance, the reasons pertaining to the meteorology which have an effect on the temperature for any given day tend to have some affect on the next day's climate. Hence, the observations of the past temperature are helpful for predicting temperatures for the following days. • A time series can be deterministic if there are no haphazard or feasible features but goes in a set and foreseeable manner. The data gathered during the classical physics experiment like showing Newton's Law of Motion, is one example of a deterministic time series. The stochastic type of series is more appropriate to the econometric function. Stochastic variables contain undefined or arbitrary viewpoint. Though the worth of each study cannot be precisely foreseen, calculating the various observations could follow the expected method. These methods can be explained through the statistical models. According to these models, studies differ erratically on the underlying mean value whtch is the role of time. Time series data can be put in the following categories: one or more performance factors; trend, seasonality, cyclical function and random sound. Various kinds of time series predicting models give forecasts through extrapolating the previous performance of the values of a specified \'l!riable of interest. Consecutive study in

econometric times series are generally not free and forecast can be made on the basis of last observations. Although precise predictions can be made with deterministic time series, predictions of stochastic time series are restricted to 'conditional statements regarding the future on the basis of particular hypothesis.' Armstrong (2001) says, "The basic Assumption is that the variable ui!! continue in the future as it has behaved in the past. " Particularly, the time series predictions are suitable for stochastic type of data in

which the fundamental root cause of variation like, trend, cyclical performance, seasonality, and uneven variations, do not change radically m time. Therefore, modeling is considered to be more suitable temporarily instead of permanent predictions.

Answer the following question.

Q1. Write briefly on time series analysis. (Hint: recognizing the quality of the phenomenon shown by the series of studies, and, both the aims need the plan of the viewed time series data is recognized and somewhat officially explained)

Problem of Transportation Routes (20 Marks)

The N&C Bank in Thailand is one of the biggest banks. There are 377 branches in Bangkok and 3 distribution centers. Presently, it has experienced drivers who take to the transportation routes. 27 vehicles are used on the 29 routes whose capacity is the same. Two of the vehicles do overtime with taking two trips each day. Some of the problems faced by N&S and formulated are: Each trip will begin from its respective depot and end there. The route will remain the same both morning and evening. The travelling time taken between each branch is a known location and correct. The company is aware of 'the demand for capital of each branch. Time of processing for every stop is same. for each branch. Some of the limitations of this problem are: The volume of each vehicle is firmly implemented by the insurance value per trip. Each branch's hours of functioning depends upon its location. If the location is in the department store, then the working hours will be from 11 am to 8 pin. If the location is anywhere else, the working hours would be from 8.30 am to 3.30 pm. The processing capacity of every depot or the distribution center (DC) is diverse at the ratio of 50:30:20.

Each distribution center works from 8.00 am to 5.00 pm. N&C aims at increasing the transportation services along with the current resources. N&C has three distribution centers which look after the picking up and delivery of cash to and from every branch each day at different timings. The most appropriate method for this problem would be the multiple depot routing problems with time limit.Nevertheless, the new routes can bring changes in everyday process, i.e., change in requirements, processing time, etc, hence, N&C requires a method to give results in a short time operations. Two main methods are used. First, development problem •is utilized. and capacitate VRPTW (vehicle routing problem with time) is utilized later. The assignment problem gathers 377 branches into 3 groups, with each belonging to each distribution center and VRP'IW makes daily routes for each distribution center. Consignment Problem method is used for giving the tasks to the agents mating their positions, which can give a very competent result. Vehicle rouong problem is the CVRP (capacitate vehicle routing problem), a pr' Herb where all its customers need to be satisfied, awareness of dumbfounds, and identifying all vetides, constrained capacity and based at a central depot. The aim is to reduce the fleet of \•vehicles and total commuting time at the same time as, total requirement of goods for each route should not go beyond the capacity of the vehicle which plies on that route. ":be most vital expansion of CVRP is the vehicle routing problem with VRPTW (time window) which should serve each customer with a particular time window.

Answer the following question.

Q1. Write a short on the transportation system of N&C bank. (Hint: it has experienced drivers who take to the transportation routes. 27 vehicles are used on the 29 routes whose capacity is the same,N&C has three distribution centers which look after the picking up and delivery of cash to and from every branch each day at different timings)

Q2. What does CVRP stand for? (Hint: capacitated vehicle routing problem)

Case (20 Marks)

Restaurants can avoid losing customers because of long waiting queues. Some restaurants have chairs to help customers sit and wait, which they put on the safe side, and remove the chairs as time goes on. Nevertheless, putting waiting chair is 9ot the onl/' solution when the customers would go back and prefer going to another place, there ls a need to improve the service time. The restaurant management needs to understand the situation in a better way through numerical model. A data was taken from a restaurant in Jakarta. Little's Theorem and M/Ml queuing model was used to get the ration of arrival, service, utilization, waiting time and likelihood of probable customers. At Sushi Tei, the customers' arrival rate during the busiest time of the day is 2.22 customers/minute (cpm), while the service is 2.24 cpm. The average number of customers is 1.22 and that of utilization period is 0.991. The study of queuing or waiting lines is called the Queuing Theory. The evaluation taken after using the Queuing Theory includes expected waiting time in line, average time in the system, length of the line, anticipated number of customers being served at one time, possibility of customers that cringe, and the possibility of the system in some states, like unoccupied or occupied. This data was taken after the interviewing the restaurant manager of Sushi Tei, and the data collected through the observations at the restaurant. The rate of visiting customers was taken from the restaurant. The restaurant used to keep a record of its everyday routine work. The manager of the restaurant was interviewed to find about the capacity of the restaurant, number of waiters and waitresses working there, and also the number of cooks. It was observed that the M/M/1 operation was best suited for the queuing model of the restaurant. This shows , that the time of arrival and service are distributed proportionately. The system .of the restaurant contained only one server. It was observed that, though there were a number of waitresses in the restaurant, only one cook was there to serve all the customers. According to the analysis done on the functioning of the restaurant, on an average each customer would spend 55 minutes, the length of the queue is approx. 36 customers, and the waiting time rs apprc;. 15 i ! minutes on average. It is seen that the waiting time is not different from the theoretical waiting time. it is assumed that the possible customers will begin to withdraw on seeing more than 10 people ahead of them in the queue. It is also observed that, on average, the customer can only tolerate 40 people in the queue. Since the capacity of the restaurant is for 120 customers when fully occupied, the possibility of 10 customers in a queue can be calculated as against 130 in the system, i.e., 120 occupants in the restaurant and 10 or more waiting in the queue. A simulation model will be developed for the restaurant. Through this simulation, the analytical model results can be attained. Also, the simulation model will help in adding more difficulty so the model can reflect the exact operation of the restaurant more personally.

Answer the following question.

Q1. What are the reasons that show that DHS is incapable in evaluating the risks of national security? (Hint: while the CS needs to evaluate expenditure benefits• for government regulations, such evaluation seem to have not been done for homeland security in general, DHS is not able to take up such evaluation.)

Q2. The government spent nearly 141.6 billion dollars each year on (Hint: homeland security)

CASE STUDY (20 Marks)

Mr Sehwag invests Rs 2000 every year with a company, which pays interest at 10% p.a. He allows his deposit to accumulate at C.I. Find the amount to the credit of the person at the end of 5th year.

Answer the following question.

Q1. What is the Time Value of Money concept?

Q2. What do you mean by present value of money?

Q3. What is the Future Value of money?

Q4. What the amount to be credited at the end of 5th year.

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

0 notes

scentedbeardgarden · 4 years ago

Quote

Data scientist course

0 notes

statisticshomeworktutors-blog · 8 years ago

Text

Random Variable and Distribution Function Assignments

Random Variable and Distribution Function projects are used to analyze the differences among groups. Even though the cumulative distribution function is defined for every random variable, we will often use other characterizations, namely, the mass function for discrete random variable and the density function for continuous random variables. We at www.statisticshomeworktutors.com assure to help you in your Random Variable and Distribution Function homework or Random Variable and Distribution Function assignments help. We can help you in deep understanding of the subject knowledge, which our experts are well versed with. We have a committed group of well versed Random Variable and Distribution Function experts and Random Variable and Distribution Function tutors who provide quality work par excellence.

#Random Variable and Distribution Function Assignment Help Random Variable and Distribution Function Project Help Random Variable and Distrib

0 notes

statisticshomeworktutors-blog · 7 years ago

Text

RANDOM VARIABLE AND DISTRIBUTION FUNCTION ASSIGNMENT PROJECT HELP

probability and statistics, a random variable, random quantity, aleatory variable or stochastic variable is a variable whose value is subject to variations due to chance. A random variable can take on a set of possible different values, each with an associated probability, in contrast to other mathematical variables. We have a team of highly qualified & dedicated expert who are available to help you excel in your Random Variable and Distribution Function assignments. Statisticshomeworktutors.com assures to provide you with well-structured and well-formatted solutions and our deliveries have always been on time whether it’s a day’s deadline or long. You can anytime buy Random Variable and Distribution Function assignments online through us and we assure to build your career with success and prosperity.

#Random Variable and Distribution Function Assignment Help Random Variable and Distribution Function Homework Help Random Variable and Distri

0 notes

freewhispersmaker · 8 years ago

Text

Decision Analysis

>> CLICK HERE TO ORDER 100% ORIGINAL PAPERS FROM AcademicWritersBay.com <<<</strong>

The post Decision Analysis appeared first on Academic Writers BAy.

#Get a 100% Non-Plagiarized Essay For As Low As 9 USD Per Page - 6 Hours Delivery Available - Good Gr

0 notes

freewhispersmaker · 8 years ago

Text

Task QUESTION 1 Decision Analysis

• Task QUESTION 1 Decision Analysis Guide to marks: 20 marks- 6 for a, 2 each for b1 & b2, 3 each for b3 & b4, 4 for b5 Show all calculations to support your answers. You may follow the methods shown in the mp4 on Decision Analysis for a way to do part (b) of this question if you wish. (a) Discuss the differences among decision making under certainty, under risk and under complete uncertainty. (b) Bikram Shrestha is considering investing some money that he inherited. The following payoff matrix gives the profits that would be realised during the next year for each of the investments that Bikram is considering. Good Economy Poor Economy Share market $80,000 ($20,000) Bonds 30,000 20,000 Real estate 25,000 15,000

>> CLICK HERE TO ORDER 100% ORIGINAL PAPERS FROM AcademicWritersBay.com <<<</strong>

The post Task QUESTION 1 Decision Analysis appeared first on Academic Writers BAy.

#Get a 100% Non-Plagiarized Essay For As Low As 9 USD Per Page - 6 Hours Delivery Available - Good Gr

0 notes

freewhispersmaker · 8 years ago

Link

>> CLICK HERE TO ORDER 100% ORIGINAL PAPERS FROM AcademicWritersBay.com <<<</strong>

The post Task QUESTION 1 Decision Analysis appeared first on Academic Writers BAy.

0 notes

homestudyhelp365-blog · 8 years ago

Text

Write a short on the transportation system of N&C bank. (Hint it has experienced drivers who take to the transportation routes. 27 vehicles are used on the 29 routes whose capacity

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

Quantitative Methods

Case Studies

Finoplastika Industries Ltd, Nigeria (20 Marks)

Answer the following question.

Problem of Transportation Routes (20 Marks)

Answer the following question.

Q2. What does CVRP stand for? (Hint: capacitated vehicle routing problem)

Case (20 Marks)

Answer the following question.

Q2. The government spent nearly 141.6 billion dollars each year on (Hint: homeland security)

CASE STUDY (20 Marks)

Mr Sehwag invests Rs 2000 every year with a company, which pays interest at 10% p.a. He allows his deposit to accumulate at C.I. Find the amount to the credit of the person at the end of 5th year.

Answer the following question.

Q1. What is the Time Value of Money concept?

Q2. What do you mean by present value of money?

Q3. What is the Future Value of money?

Q4. What the amount to be credited at the end of 5th year.

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

o�Ra�0o

0 notes

homestudyhelp365-blog · 8 years ago

Text

What the amount to be credited at the end of 5th year

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

Quantitative Methods

Case Studies

Finoplastika Industries Ltd, Nigeria (20 Marks)

Answer the following question.

Problem of Transportation Routes (20 Marks)

Answer the following question.

Q2. What does CVRP stand for? (Hint: capacitated vehicle routing problem)

Case (20 Marks)

Answer the following question.

Q2. The government spent nearly 141.6 billion dollars each year on (Hint: homeland security)

CASE STUDY (20 Marks)

Mr Sehwag invests Rs 2000 every year with a company, which pays interest at 10% p.a. He allows his deposit to accumulate at C.I. Find the amount to the credit of the person at the end of 5th year.

Answer the following question.

Q1. What is the Time Value of Money concept?

Q2. What do you mean by present value of money?

Q3. What is the Future Value of money?

Q4. What the amount to be credited at the end of 5th year.

Assignment Solutions, Case study Answer sheets

Project Report and Thesis - Contact

[email protected]

www.mbacasestudyanswers.com

ARAVIND – 09901366442 – 09902787224

0 notes