Question: MNGT 379: Business Analytics Chapter 4, Problem Set 1 1. A realtor wishes to investigate the relationship between the selling price and the size and

MNGT 379: Business Analytics Chapter 4, Problem Set 1 1. A realtor wishes to investigate the relationship between the selling price and the size and age of the house in Geen City. She took a random sample of 10 houses from those sold in the last three months and recorded the prices (in $1,000, denoted by variable y), their sizes (in square feet, denoted by variable x1) and ages (in years, denoted by variable x2). Below are the sample data and the output of the regression analysis from Excel. House Price Size Age 1 2 3 4 5 6 7 8 9 10 229.6 286.0 265.6 301.6 300.4 324.4 348.4 362.8 338.8 402.4 845 1,500 1,350 1,800 1,820 1,930 2,000 2,400 1,900 3,450 65 47 55 37 38 30 18 10 22 3 Page 1 of 4 Based on the Excel output, answer the following questions. 1) Give an estimated regression model (equation). 2) Interpret the business and economic meaning of the coefficients b1 and b2 for this problem. 3) Give the value of the coefficient of determination, and interpret the business and economic meaning of the value of the coefficient of determination in this problem. 4) Predict the selling price of a house that is 25 years old and has 2,200 square feet. Page 2 of 4 5) Test whether there is an overall linear relationship between the price and the variables size and age. Follow the 6-step procedure for hypothesis testing. Use = 0.05. Step 1. Define the hypotheses. Step 2. Specify the level of significance . Step 3. Compute the value of the test statistic. Step 4. Compute the p-value. Step 5. Determine whether to reject H0. Step 6. Interpret the statistical conclusion in the context of the application. Page 3 of 4 6) Test whether there is a linear relationship between the price and the size of the house. Follow the 6-step procedure for hypothesis testing. Use = 0.05. Step 1. Define the hypotheses. Step 2. Specify the level of significance . Step 3. Compute the value of the test statistic. Step 4. Compute the p-value. Step 5. Determine whether to reject H0. Step 6. Interpret the statistical conclusion in the context of the application. Page 4 of 4

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