Week 4

DQ 1

Simple Regression Analysis.

Use the data in the chart to answer the questions below. The data indicates the number of “sick days” appliance installers take during a three month period, and the number of complaints filed by customers during the same interval. Use the Analysis Toolpak in Excel to perform this simple regression and answer the questions.

a. Is the correlation between number of sick days and number of customer complaints statistically significant?

b. What is the best prediction for the number of complaints that will be registered for an installer who takes five sick days during the period?

Use Excel to help you answer the questions in the forum but do not attach your Excel document to the discussion post.

DQ 2

Multiple Regression Analysis.

Develop a multiple linear regression equation that describes the relationship between tenure and the other variables in the chart above. Use the Analysis Toolpak located in Excel to perform this multiple regression.

Do these two variables explain a reasonable amount of the variation in the dependent variable?

Estimate the tenure of someone that could have $5.8($k) and 15 years of job satisfaction. Make sure to state your multiple regression equation in your example. What are some of things that you can estimate from the model? How effective is evaluating the R-squared of the model? What is the relationship between the independent and dependent variables?

Use Excel to help you answer the questions in the forum but do not attach your Excel document to the discussion post.

Guided Response: Review several of your classmates’ postings. Respond to at least two classmates by commenting on how this information might be used to make business decisions.

Problem Set Week Four.

Complete the problems below and submit your work in one Word document. Be sure to show all of your work and clearly label all calculations. Calculations completed in Excel must be copied and pasted into a single Word document. No Excel documents will be graded.

TIP: For help copying and pasting information from Excel to Word go to http://office.microsoft.com/en-us/word-help/copy-excel-data-or-charts-to-word-HP010198874.aspx or watch the “Excel Tips – Tip#48: Copy from Excel to Word” found in Week One Recommended Resources.

Problem One

The manager of a catering company is using the number of people in the party to predict the cost of the drinks that are required for the event. The following are the data for 12 recently catered events:

Complete the calculations below using this data. Show all of your work and clearly label each of your calculations.

a. Provide a scatterplot

b. Calculate a linear regression

c. Calculate the residuals

d. Calculate the correlation between the two variables

e. Calculate the mean, median, and standard deviation of the number of people and cost of drinks

For additional assistance with these calculations reference the Recommended Materials for Week Four.

Problem Two

You are a real estate agent and you are trying to predict home prices for your clients that want to list their house for sale. You have a very small city without much data. You will need to use the data that you have available for the past year on homes that have been sold.

Complete the calculations below using this data. Show all of your work and clearly label each of your calculations.

Conduct a multiple regression analysis to predict home prices. In your analysis complete the following:

a. Calculate the multiple regression analysis and report your data.

b. Determine the list price for your client’s home if it has three bedrooms, three bathrooms, and 1900 square footage. Provide your analysis and show all of your calculations.

For additional assistance with these calculations reference the Recommended Materials for Week Four.

QUiz

1. Question : With reference to problem 1, what statistic determines the correlation of experience with productivity, controlling for age in experience?

Student Answer: The regression coefficient.

The standard error of the estimate.

The semi-partial correlation.

The multiple correlation.

Points Received: 1 of 1

Comments:

2. Question : In a problem where interest rates and growth of the economy are used to predict consumer spending, which of the following will increase prediction error?

Student Answer: More homogeneous data.

A small sample.

Reducing the number of predictors.

Adding more data on interest rates.

Points Received: 1 of 1

Comments:

3. Question : With reference to problem 3, how is the regression constant or the a value interpreted?

Student Answer: It indicates the amount of error in the prediction.

It gauges the number of computers when efficiency is zero.

Office efficiency with no computers, controlling for the number of workers.

Number of workers, controlling for number of computers in the office.

Points Received: 1 of 1

Comments:

4. Question : Which of the following is a problem in simple regression?

Student Answer: What is the correlation between years of experience and productivity?

Is there a significant difference in job satisfaction between men and women?

Can age predict length of tenure in a position?

What is the proportion of variance in productivity explained by experience?

Points Received: 1 of 1

Comments:

5. Question : In a problem where average temperature and number of daylight hours are used to predict energy consumption in homes, what does the standard error of multiple estimate gauge?

Student Answer: Prediction error

The value of the first predictor.

The error in the second predictor.

The correlation of the criterion with the predictors.

Points Received: 1 of 1

Comments:

6. Question : What does “shrinkage” mean in reference to regression solutions?

Student Answer: A reduction in the error term.

The solution works less well with new data.

The sample size has been reduced.

A reduction in the number of predictor variables.

Points Received: 1 of 1

Comments:

7. Question : The degree to which years of education and years of experience together correlate with annual salary is indicated in multiple correlation.

Student Answer: True

False

Points Received: 1 of 1

Comments:

8. Question : The criterion variable in regression is the variable used to predict the value of y.

Student Answer: True

False

Points Received: 1 of 1

Comments:

9. Question : Which of the following are consistent with the requirements of simple regression?

Student Answer: Using sales volume to predict dollar profits.

Using the sales associate’s ranking to predict job satisfaction.

Using the employee’s gender to predict their productivity ranking.

Using the employee’s gender to predict marital status.

Points Received: 1 of 1

Comments:

10. Question : Larger sample diminish the standard error of the estimate.

Student Answer: True

False

Points Received: 1 of 1

Week 4

DQ 1

Simple Regression Analysis.

Use the data in the chart to answer the questions below. The data indicates the number of “sick days” appliance installers take during a three month period, and the number of complaints filed by customers during the same interval. Use the Analysis Toolpak in Excel to perform this simple regression and answer the questions.

a. Is the correlation between number of sick days and number of customer complaints statistically significant?

b. What is the best prediction for the number of complaints that will be registered for an installer who takes five sick days during the period?

Use Excel to help you answer the questions in the forum but do not attach your Excel document to the discussion post.

DQ 2

Multiple Regression Analysis.

Develop a multiple linear regression equation that describes the relationship between tenure and the other variables in the chart above. Use the Analysis Toolpak located in Excel to perform this multiple regression.

Do these two variables explain a reasonable amount of the variation in the dependent variable?

Estimate the tenure of someone that could have $5.8($k) and 15 years of job satisfaction. Make sure to state your multiple regression equation in your example. What are some of things that you can estimate from the model? How effective is evaluating the R-squared of the model? What is the relationship between the independent and dependent variables?

Guided Response: Review several of your classmates’ postings. Respond to at least two classmates by commenting on how this information might be used to make business decisions.

Problem Set Week Four.

Complete the problems below and submit your work in one Word document. Be sure to show all of your work and clearly label all calculations. Calculations completed in Excel must be copied and pasted into a single Word document. No Excel documents will be graded.

TIP: For help copying and pasting information from Excel to Word go to http://office.microsoft.com/en-us/word-help/copy-excel-data-or-charts-to-word-HP010198874.aspx or watch the “Excel Tips – Tip#48: Copy from Excel to Word” found in Week One Recommended Resources.

Problem One

The manager of a catering company is using the number of people in the party to predict the cost of the drinks that are required for the event. The following are the data for 12 recently catered events:

Complete the calculations below using this data. Show all of your work and clearly label each of your calculations.

a. Provide a scatterplot

b. Calculate a linear regression

c. Calculate the residuals

d. Calculate the correlation between the two variables

e. Calculate the mean, median, and standard deviation of the number of people and cost of drinks

For additional assistance with these calculations reference the Recommended Materials for Week Four.

Problem Two

You are a real estate agent and you are trying to predict home prices for your clients that want to list their house for sale. You have a very small city without much data. You will need to use the data that you have available for the past year on homes that have been sold.

Conduct a multiple regression analysis to predict home prices. In your analysis complete the following:

a. Calculate the multiple regression analysis and report your data.

b. Determine the list price for your client’s home if it has three bedrooms, three bathrooms, and 1900 square footage. Provide your analysis and show all of your calculations.

For additional assistance with these calculations reference the Recommended Materials for Week Four.

QUiz

1. Question : With reference to problem 1, what statistic determines the correlation of experience with productivity, controlling for age in experience?

Student Answer: The regression coefficient.

The standard error of the estimate.

The semi-partial correlation.

The multiple correlation.

Points Received: 1 of 1

Comments:

2. Question : In a problem where interest rates and growth of the economy are used to predict consumer spending, which of the following will increase prediction error?

Student Answer: More homogeneous data.

A small sample.

Reducing the number of predictors.

Adding more data on interest rates.

Points Received: 1 of 1

Comments:

3. Question : With reference to problem 3, how is the regression constant or the a value interpreted?

Student Answer: It indicates the amount of error in the prediction.

It gauges the number of computers when efficiency is zero.

Office efficiency with no computers, controlling for the number of workers.

Number of workers, controlling for number of computers in the office.

Points Received: 1 of 1

Comments:

4. Question : Which of the following is a problem in simple regression?

Student Answer: What is the correlation between years of experience and productivity?

Is there a significant difference in job satisfaction between men and women?

Can age predict length of tenure in a position?

What is the proportion of variance in productivity explained by experience?

Points Received: 1 of 1

Comments:

5. Question : In a problem where average temperature and number of daylight hours are used to predict energy consumption in homes, what does the standard error of multiple estimate gauge?

Student Answer: Prediction error

The value of the first predictor.

The error in the second predictor.

The correlation of the criterion with the predictors.

Points Received: 1 of 1

Comments:

6. Question : What does “shrinkage” mean in reference to regression solutions?

Student Answer: A reduction in the error term.

The solution works less well with new data.

The sample size has been reduced.

A reduction in the number of predictor variables.

Points Received: 1 of 1

Comments:

7. Question : The degree to which years of education and years of experience together correlate with annual salary is indicated in multiple correlation.

Student Answer: True

False

Points Received: 1 of 1

Comments:

8. Question : The criterion variable in regression is the variable used to predict the value of y.

Student Answer: True

False

Points Received: 1 of 1

Comments:

9. Question : Which of the following are consistent with the requirements of simple regression?

Student Answer: Using sales volume to predict dollar profits.

Using the sales associate’s ranking to predict job satisfaction.

Using the employee’s gender to predict their productivity ranking.

Using the employee’s gender to predict marital status.

Points Received: 1 of 1

Comments:

10. Question : Larger sample diminish the standard error of the estimate.

Student Answer: True

False

Points Received: 1 of 1