Project #26252 - Applied Decision Making

 

This assignment consists of two parts. Part A is two sets (5 questions per set) of short answer questions. Part B is two sets (2 questions per set) of problems/applications involving excel sheets.

You MUST provide interpretation of results and describe conclusions.

 

PART ONE

 

 

 

Set One:

 

 

 

1.)  Explain the difference between the null hypothesis and alternative hypothesis. Which one can be proven in a statistical sense?

 

 

 

2.)  How can you determine when to use a lower oneâ€Âtailed test of hypothesis versus an upper oneâ€Âtailed test?

 

 

 

3.)  Explain the purpose of the chiâ€Âsquare test for independence. Provide some practical examples where this test might be used in business.

 

 

 

4.)  Explain the difference between simple and multiple linear regression.

 

 

 

5.)  Explain what the coefficient of determination, R^2 (R-squared), measures. How is it related to the sample correlation coefficient?

 

 

 

 

 

Set Two:

 

 

 

1.)  Summarize statistical methods used in forecasting and the types of time series to which they are most appropriate.

 

 

 

2.)  Summarize some of the practical issues in using forecasting tools and approaches.

 

 

 

3.)  Describe the steps involved in applying statistical process control.

 

 

 

4.)  List the principal rules for examining a control chart to determine if the process is in control.

 

 

 

5.)  What is process capability? How is it measured?

 

 

 

 

 

 

 

PART TWO

 

 

 

Set One

 

 

 

Solve Problem and Applications:Solve Problem and Applications:ch 5- prob1 (use excel file Call Center Data), and ch 6- prob12 (Home market values).


 

 

 

5-1: 1. Call centers typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank’s call centers in the Excel file Call Center Data . In writing an article about call center working conditions, a reporter has claimed that the average tenure is no more than two years. Formulate and test a hypothesis using these data to determine if this claim can be disputed. Solution Tip: You need to write mathematical test of hypothesis statements and apply the test of hypothesis steps.


 

 

 

 

 

 

 

 

 

6-12: 2. Using the data in the Excel file Home Market Value, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. Find a 95% confidence interval for the mean market value for houses that are 30 years old and have 1,800 square feet and a 95% prediction interval for a house that is 30 years old with 1,800 square feet.

Please be sure your work is organized, legible, and your responses are substantive. You need to submit all details of your work including excel sheets used to arrive to the solution. It is not enough to attach your excel sheet. You MUST provide interpretation of results and describe conclusions.

 

 

 

Set Two

 

 

 

Solve Problem and Applications: ch7- prob 12, and ch 8- prob 4 at the end of chapters 7 and 8 in your textbook.

 

Please be sure your work is organized, legible, and your responses are substantive. You need to submit all details of your work including excel sheets used to arrive to the solution. It is not enough to attach your excel sheet. You MUST provide interpretation of results and describe conclusions.

7-12: Develop a multiple regression model with categorical
variables that incorporate seasonality for forecasting sales using the last three years of data in the Excel file New Car Sales.

Tips for problem 7-12:
This is a multiple regression problem based on monthly data. You will need to create dummy variables for the months to represent seasonality in the model.

Here is a video about the concept:

http://www.youtube.com/watch?v=H07l1zgM-cw

Here is part of what want to do:

 

Year

Month

Units

t

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

1

Jan

39,810

1

0

0

0

0

0

0

0

0

0

0

0

1

Feb

40,081

2

1

0

0

0

0

0

0

0

0

0

0

1

Mar

47,440

3

0

1

0

0

0

0

0

0

0

0

0

1

Apr

47,297

4

0

0

1

0

0

0

0

0

0

0

0

1

May

49,211

5

0

0

0

1

0

0

0

0

0

0

0

 


You will fill all entries for three years, then run regression in excl.



 

 

 

8-4: If 30 samples of 100 items are tested for nonconformity, and 95 of the 3,000 items are defective, find the upper and lower control limits for a p -chart.

 

 

 

 

 

 

 

 

Subject Business
Due By (Pacific Time) 03/30/2014 07:30 pm
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