The financial manager at Choice Clothing noticed that the company's sales revenues (Y) (in 1,000) were not the same from month to month. The marketing manager established that the company's advertising expenditures (X) (in 1,000) also varied from month to month. They were interested to determine whether a relationship existed between sales and advertising expenditure during 16 months. The slope and intercept were computed and the regression equation is y=110.02+2.32x. What is the estimated monthly sales revenue (in rands) if the company invests R89,160 in advertising in a particular month (rounded off to two decimals)?    A. R206 961.22

While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.385*(age) + 5.218. If a customer is 44.315 years old and they make an average of 11.239 claims per year, the residual is -11.04. Interpret this residual in terms of the problem.   Question 10 options:   1)  The number of claims per year is 11.04 claims less than what we would expect.   2)  The age is 11.04 years larger than what we would expect.   3)  The age is 11.04 years less than what we would expect.   4)  The number of claims per year is 11.239 claims less than what we would expect.   5)  The number of claims per year is 11.04 claims…

The following data show the brand, price (S), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ý = 22.522 + 0.335x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 78 B 150 73 95 63 70 58 E 70 38 35 26 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = (b) Compute the coefficient of determination rt. (Round your answer to three decimal places.) 12 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. O The least squares line did not provide a good fit as a small proportion of the variability in y…

The applet displays a scatterplot with the following points: (7,10),(27,35),(24,25),(8,12),(10,19),(15,22). Identify the slope of the regression line, intercept of the regression line, and correlation coefficient. Report your answers accurate to within two decimal places.

The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…

A researcher wanted to predict the sodium content (in milligrams) of beef hot dogs by looking at the calorie content.  His findings from a sample of 10 beef hot dogs are summarized below. The regression equation for his data is          ŷ= -299.48 + 4.35 x    Calories  186  181  176  149  184  190  158  139  175  148  Sodium  495  477  425  322  482  587  370  322  479  375                                                                                 Interpret the slope in terms of this problem.  If appropriate, find the sodium content if the calorie content is 170. If not, why?  If appropriate, find the sodium content if the calorie content is 136. If not, why?

A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression equation ŷ = 4.9x + 15.2, where x represents attendance (in thousands) and ŷ is the predicted number of wins. Which statement best describes the meaning of the slope of the regression line?  For each increase in attendance by 1,000, the predicted number of wins increases by 4.9. For each increase in attendance by 1,000, the predicted number of wins increases by 15.2. For each increase in the number of wins by 1, the predicted attendance increases by 4,900. For each increase in the number of wins by 1, the predicted attendance increases by 15,200.

The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…

A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.

An admissions counselor is looking to determine an equation that relates the graduate grade point averages of students who are newly admitted to an academic program with their undergraduate GPA, their GRE scores, and the number of years they have been out of college. What is the correct format for a multiple regression equation? Select the correct answer below:   yˆ=b0+b1x1+b2x2+b3x3   yˆ=b1x1+b2x2+b3x3   yˆ=b0+b1x1+b2x2+b3x3+b4x4   yˆ=b0+b1x1+b2x2