![]() The outliers are scattered and not serious. (c)Answer: R2 = 0.490 se = 228.297 Term Estimate Std Error t Ratio Prob>|t| Intercept 1262 236 5.34 0 Volume (Gallons) 0.240 0.073 3.28 0.003 Car Washes 0.864 0.382 2.26 0.032 In JMP hit Fit Model, put Sales in Y and Volume and Washes put in ADD (d)Answer: Yes. This is because the correlation is the greatest and in the graph these two have the most linear relation The data indicate that Volume is somewhat more predictive of Sales than Washes are. (b)Answers: Sales (Dollars) Volume (Gallons) Car Washes Sales (Dollars) 1.000 0.628 0.536 Volume (Gallons) 0.628 1.000 0.400 Car Washes 0.536 0.400 1.000 (Round to three decimal places as needed.) Go to JMP and hit ANALYZE, then press MULTIVARIATE METHODS, then press on MULTRIVIATE The largest correlation is between Sales and Volume. The scatterplots appear to be reasonably straight except for one or two possible outliers. The scatterplot does not have any unusual features. (a)Answers: The scatterplot does not have any unusual features. In your interpretation, include a range for the effect of this variable. (Use a 95% confidence interval.) Interpret carefully the estimated slope for the number of car washes. (e) Assume that the model meets the conditions for the MRM. Round all probabilities to three decimal places.) (d) Does the fitted model meet the conditions for using the multiple regression model (MRM) for inference? Choose the correct answer below. Round all test statistics to two decimal places. Round the coefficient and standard error of the Volume and Car Washes terms to three decimal places. Round the coefficient and standard error of the Intercept term to the nearest integer. (Round R2mand se to three decimal places. Show a summary of the fitted model. (Save the diagnostic for part d.) Complete the table below. (c) Fit the multiple regression of sales on volume and the number of car washes. Which correlation is the largest? Explain why this correlation is larger than the others. Which correlation is largest? Explain why this correlation is larger than the others. Are there any unusual features in the data? Do the relevant plots appear straight enough for multiple regression? (b) Find the correlation between each pair of variables. Are there any unusual features in the data? Examine the scatterplot to the right. Do you notice any unusual features in the data? Do the relevant plots appear straight enough for multiple regression? Examine the scatterplot to the right. ![]() (a) Examine scatterplots of the response versus the two explanatory variables as well as the scatterplot between the responses. The explanatory variable Volume gives the number of gallons sold, and Washes gives the number of car washes sold at the station. The response Sales gives the dollar sales of the convenience store. This particular station sells gas, and it also has a convenience store and a car wash. Each row of 3 columns summarizes sales for one day. 38-T These data describe the sales over time at a franchise outlet of a major oil company.
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