## Spreadsheet Modeling and Decision Analysis Study Set 2

Statistics

## Quiz 9 :

Regression Analysis

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Q42 Q42 Q42

An analyst has identified 3 independent variables (X

_{1}, X_{2}, X_{3}) which might be used to predict Y. He has computed the regression equations using all combinations of the variables and the results are summarized in the following table. Why is the R^{2}value for the X_{3}model the same as the R^{2}value for the X_{1}and X_{3}model, but the Adjusted R^{2}values differ?Free

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Q47 Q47 Q47

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. What is the estimated regression function for this problem? Explain what the terms in your equation mean.Free

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Q48 Q48 Q48

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. Predict the mean number of labor hours for a batch of 5 parts.Free

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Q49 Q49 Q49

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. Provide a rough 95% confidence interval on the number of labor hours for a batch of 5 parts.Free

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Q50 Q50 Q50

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. Test the significance of the model and explain which values you used to reach your conclusions.Free

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Q51 Q51 Q51

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet.Free

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Q52 Q52 Q52

Exhibit 9.1
The following questions are based on the problem description and spreadsheet below.
A company has built a regression model to predict the number of labor hours (Y

_{i}) required to process a batch of parts (X_{i}). It has developed the following Excel spreadsheet of the results. -Refer to Exhibit 9.1. Interpret the meaning of R Square in cell B3 of the spreadsheet.Free

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Q53 Q53 Q53

The company would like to build a prediction interval on the time for a new batch of 8 parts. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

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Q54 Q54 Q54

Exhibit 9.2
The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.2. What is the estimated regression function for this problem? Explain what the terms in your equation mean.

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Q55 Q55 Q55

Exhibit 9.2
The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.2. Predict the mean pressure for a temperature of 120 degrees.

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Q56 Q56 Q56

Exhibit 9.2
The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.2. Test the significance of the model and explain which values you used to reach your conclusions.

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Q57 Q57 Q57

Exhibit 9.2
The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.2. Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet.

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Q58 Q58 Q58

Exhibit 9.2
The following questions are based on the problem description and spreadsheet below.
A paint manufacturer is interested in knowing how much pressure (in pounds per square inch, PSI) builds up inside aerosol cans at various temperatures (degrees Fahrenheit). It has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.2. Interpret the meaning of R Square in cell B3 of the spreadsheet.

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Q59 Q59 Q59

The company would like to build a prediction interval on the pressure for a can with a temperature of 125 degrees. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

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Q60 Q60 Q60

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.3. What is the estimated regression function for this problem? Explain what the terms in your equation mean

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Q61 Q61 Q61

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.3. Predict the mean number of calories consumed by a 19 year old man.

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Q62 Q62 Q62

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.3. Test the significance of the model and explain which values you used to reach your conclusions.

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Q63 Q63 Q63

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.3. Interpret the meaning of the "Lower 95%" and "Upper 95%" terms in cells F16:G16 of the spreadsheet.

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Q64 Q64 Q64

Exhibit 9.3
The following questions are based on the problem description and spreadsheet below.
A researcher is interested in determining how many calories young men consume. She measured the age of the individuals and recorded how much food they ate each day for a month. The average daily consumption was recorded as the dependent variable. She has developed the following Excel spreadsheet of the results.
-Refer to Exhibit 9.3. Interpret the meaning of R square in cell B3 of the spreadsheet.

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Q65 Q65 Q65

The researcher would like to build a prediction interval on the calories consumed by an 18 year old man. What formula should be entered in cells B17:F21 of the following spreadsheet to compute this prediction interval? Partial results of the Regression analysis of the data are provided below.

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Q66 Q66 Q66

Exhibit 9.4
The following questions are based on the problem description and spreadsheet below.
A charitable organization wants to determine what type of people donate to charities like itself. The charity felt that a person's education (in years), annual income, ($1,000) and the number of children the person had were important variables to consider. The charity developed regression models for all of the possible combinations of these three variables but does not know what to do with the results.
-Refer to Exhibit 9.4. Based on the data in the table which is the best model for the charity to use? Explain which values you used to reach your conclusion.

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Q67 Q67 Q67

Exhibit 9.4
The following questions are based on the problem description and spreadsheet below.
A charitable organization wants to determine what type of people donate to charities like itself. The charity felt that a person's education (in years), annual income, ($1,000) and the number of children the person had were important variables to consider. The charity developed regression models for all of the possible combinations of these three variables but does not know what to do with the results.
-Refer to Exhibit 9.4. Predict the mean donation by a person with 16 years of education, $90,000 annual income and 2 children. Use a full model based on data from the table.

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Q68 Q68 Q68

Exhibit 9.5
The following questions are based on the description and spreadsheet below.
An analyst has identified 3 independent variables (X

_{1}, X_{2},X_{3}) which might be used to predict Y. He has computed the regression equations using all of the variables and the results are summarized in the following table. -Refer to Exhibit 9.5. Based on the data in the table which is the best model for the charity to use? Explain which values you used to reach your conclusion.Free

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Q69 Q69 Q69

Exhibit 9.5
The following questions are based on the description and spreadsheet below.
An analyst has identified 3 independent variables (X

_{1}, X_{2},X_{3}) which might be used to predict Y. He has computed the regression equations using all of the variables and the results are summarized in the following table. -Refer to Exhibit 9.5. Predict the mean value based on (X_{1}, X_{2}, X_{3}) = (3, 32, 50). Use the best predictive model based on data from the table.Free

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Q76 Q76 Q76

Project 9.1 Test Stand Cost Analysis Estimation
Handel Manufacturing produces test stands for various maintenance functions ranging from automobile to jet airline testing stations. For years, their cost estimating function was based on a myriad of historical data fed into a cost analysis model that produced very accurate estimates of both development and support costs for various proposed test stands. James Mudd was a recent hire into the cost analysis shop. Unfortunately, during his first week on the job, James deleted the cost analysis database and failed to maintain a backup of the model. Fortunately, all is not lost. The computer support personnel can come in Monday and retrieve the model using their system backup tapes. Unfortunately, the cost proposals for three new test stand development and deployment projects are due first thing Monday morning. Since James recently left the company, you have been tasked to complete the cost estimate portion of the proposals.
After much gnashing of your teeth, you settle down to make the best of what you initially believe is a losing situation. While studying James' files you find historical records on 25 recent test stand development and deployment projects. Rejuvenated, you realize you can succeed in this prematurely perceived doomed situation. All you need to do is analyze this historical data, develop some cost estimating functions using regression, and then use your regression models to develop estimates for the three projects due Monday. The historical data in the files is the following.
The data estimates for the three cost proposal due Monday is the following:
One thing unclear from reading the files was on the form of the cost estimating relationships contained within the lost cost analysis model. You are somewhat sure the regression models were not polynomial in form, but you are not certain of this fact. You are not even sure which variables were included in the model for development cost and which variables were included in the model for support costs. However, you are undaunted because you know you can develop accurate models and produce good cost estimates for each of the proposed projects.
Develop appropriate models for development and for support costs. Use these models to develop cost estimates for each of the new lines of test stands. For each of these cost estimates provide 95% confidence intervals for the predicted values.

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