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Minitab Output for a Multiple Regression Analysis

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13.6 Jesen, Solberg, and Zorn investigated the relationship of insider ownership, debt, and dividend policies in companies. One of their findings was that firms with high insider ownership choose lower levels of both debt and dividends. Shown here is a sample of data of these three variables for 11 different industries. Use the data to develop the equation of the regression model to predict insider ownership by debt ratio and divident payout. Comment on the regression coefficiencies.

13.8 Displayed here is the Minitab output for a multiple regression analysis. Study the ANOVA table and the t ratios and use these to discuss the strengths of the regression model and the predictors. Does this model appear to fit the data well? From the information, what recommendations would you make about the predictor variables in the model?

13.12 Use the following data to develop a regression model to predict y from x1 and x2. Comment on the output. Develop a regression model to predict y from x1 only. Compare the results of this model with those of the model using both predictors. What might you conclude by examining the output from both the regression models?

13.19 Using the regression output obtained by working Problem 13.12. comment on the overall strength of the regression model using S, R^2, and adjusted R^2.

13.22 Study the Minitab regression output that follows. How many predictors are there? What is the equation of the regression model? Discuss the strength of the model and the predictors.

13.26 The U.S. Bureau of Mines produces data on the price of minerals. Shown here are the average prices per year for several minerals over a decade. Use these data and multiple regression to produce a model to predict the average price of gold from the other variables. Comment on the results of the process.

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This solution explains the steps and comments on the output for the discussion questions in 598 words. This solutions work is prepared in an attached Excel file.

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13.6 If we designate insider ownership as y, debt ratio and dividend payout as x1 and x2 respective, we could get the following linear regression equation:
y=-0.059x1-0.118x2+17.677
-0.059 means that for every one unit increase in the debt ratio, inside ownership decreases by 0.059 unit.
-0.118 means that for every one unit increase in the dividend payout, insider ownership decreases by -0.118 unit.

13.8 From the P values for the coefficients, we could see that the P value for x1 coefficient is 0.005, less than 0.05, therefore, x1 could significantly predict the dependent variable. However, for the P value of x2 coefficient, it is 0.805, bigger than 0.05, therefore, it could not significantly predict the dependent variable. Likewise, for the P value of x3 coefficient, it is 0.230, bigger than 0.05, therefore, it could not significantly predict the dependent ...

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