Exam 9: Regression Analysis

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.

Based on the following regression output, what proportion of the total variation in Y is explained by X?

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.

Why do we create a scatter plot of the data in regression analysis?

The partial regression output below applies to the following questions. -Refer to Exhibit 9.7. What is the SS for Total?

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.

Exhibit 9.5 The following questions are based on the description and spreadsheet below. An analyst has identified 3 independent variables (X₁, X₂,X₃) 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 (X₁, X₂, X₃) = (3, 32, 50). Use the best predictive model based on data from the table.

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.

Based on the following regression output, what is the equation of the regression line?

Assume you have chosen to use all three variables in your model. Test the significance of the model and explain which values you used to reach your conclusion.

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.

Error sum of squares (ESS) is computed as

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.

The method of least squares finds parameter values that

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.

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.

R² is also referred to as

How many binary variables are required to encode a persons age group as being either young, middle-age or old? What are the variables and what are the meanings of their 0, 1 values?

The partial regression output below applies to the following questions. -Refer to Exhibit 9.6. What is the F-statistic value?

What is the formula for total sum of squares (TSS)