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Question 5: A small business enterprise makes dresses and trousers. To make a dress requires 1/2 hours of cutting and 20 minutes of stitching. To

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Question 5: A small business enterprise makes dresses and trousers. To make a dress requires 1/2 hours of cutting and 20 minutes of stitching. To make a trouser requires 15 minutes of cutting and 1/2 hour of stitching. The profit on a dress is R40 and on a pair of trousers R50. The business operates for a maximum of 8 hours per day Determine how many dresses and trousers should be made to maximize profit and what the maximum profit is. Hint: We want to maximize the following profit function Z = 40x + 50y Subject to the constraints: 2x + y = 32 2x + 3y = 48 x 20,720 Question 1: The American Heart Association collects data on the risk of strokes. A 10-year study provided data on how age and blood pressure related to the risk of strokes. Assume that following data are from a portion of this study. Risk is interpreted as the probability (times 100) that the patient will have a stroke over the next 10-year period. SUMMARY OUTPUT Regression Statistics Multiple R 0.898 R Square 0.806 Adjusted R Square 0.783 Standard Error 6.908 Observations 20 ANOVA df SS 2 3379.640297 17 811.3097028 19 4190.95 Regression Residual Total MS F 1689.82 35.40810917 47.7241 Significance F 0.001 Intercept AGE BLOOD PRESSURE Standard Coefficients Error t Stat 110.942263 16.46987072-6.73607 -1.31 0.173289862 7.58847 0.29 0.051068966 5.804008 P-value 0 0.006 0.123 Use the above Excel results to answer the following questions. a. What are the dependent and independent variables (in words)? b. Use the above Excel outputs to estimate the multiple linear regression equation c. Interpret each one of the estimated regression coefficients Bo, B1 and 32. d. What is the value of the linear correlation coefficient? Use this value to comment on whether you think a linear relationship exists between the dependent and independent variables. e. Identify and interpret the coefficient of determination f. Test the significance of the regression model at the 5% level. & Does each one of the explanatory variables do a good job of explaining changes in the risk of strokes? Explain why or why not. h. Predict the chance of stroke (risk) for a person of age is 57 years and his blood pressure of 125

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