This problem is solved by using the Minitab
a.Regression equation is
Yhat = 3.67+ 0.47 x
b. Residual plot
Option C is correct
No, assumptions of error term not satisfied.
Variance of error is not constant it is increasing function
Thank You!
The following data were used in a regression study. Obser a. Develop an estimated regression equation...
please help me with this problem im stuck The following data were used in a regression study. Observation 1 7 9 2 3 4 5 6 2 3 4 5 45 46 46 9 11 8 9 (a) Develop an estimated regression equation for these data. (round your numerical values to two decimal places.) (b) Construct a plot of the residuals. 10 D B 10 0 2 Residuals 0 + 5 8 10 B 10 O O Do the assumptions...
Consider the following data for two variables, x and y. a. Choose the correct scatter diagram with x and y. The correct scatter diagram is - _______ . Does there appear to be a linear relationship between x and y? Explain. The scatter diagram- Select your answer - some evidence of a possible linear relationship. b. Develop the estimated regression equation relating x and y. Save "predicted" and "residuals" (to 4 decimals). c. Choose the correct scatter diagram or the residuals versus y tor the estimated...
Question 1: Question 2: A statistical program is recommended. A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is = 81 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 1 80 3 97 92 107 103 111 119 128 117 136 (a) Compute the residuals. Years of Experience Annual Sales ($1,000s) Residuals 107 103 111 119 128 117 136 Construct a residual...
14 - 11 The following data were used in a regression study. Observation Nº i & Yi 1 3 24 3 5 46 57 Observation & Yi 5 2 7 6 3 8 7 2 97 9 1 a. Develop an estimated regression equation for these data. If necessary enter negative value as negative number. y = 2 (to 2 decimals)
Data for 34 cereals were examined to look for an association between fiber content and calories. A regression analysis was performed, in which the dependent variable was fiber and the independent variable was calories. Given below are graphs from the regression output. Which of the assumptions for inference are violated? Explain Click the icon to view the graphs from the regression output. Regression output graphs Is the straight enough condition satisfied? Yes 0 12 Is the independence assumption satisfied? Yes...
Using the Excel’s Regression Tool, develop the estimated regression equation to show how income (y annual income in $1000s) is related to the independent variables education (x1 level of education attained in number of years), age (x2 in years), and gender x3 dummy variable, 1= female, 0 = male. Develop the dummy variable for the gender variable first. Use the t test to test whether each of the coefficients obtained in part (a) are significant at .05 level of significance....
3. Consider the following data for two variables, x and y. 4 5 4 6 4 6 9 5 11 a. Does there appear to be a linear relationship between x and y? Explain. b. Develop the estimated regression equation relating x and y. c. Plot the standardized residuals versus g for the estimated regression equation developed in part (b). Do the model assumptions appear to be satisfied? Explain. d. Perform a logarithmic transformation on the dependent variable y. Develop...
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is y = 82 + 4x. Salesperson Years of Experience Annual Sales ($1,000s) 80 97 102 107 103 101 119 o 128 11 127 10 13 136 (a) Compute the residuals. (a) Compute the residuals. Years of Experience Annual Sales ($1,000s) Residuals 102 107 103 101 119 128 127 136 Construct a residual plot....
course NGAGE MINDTAP z and y. z | 10 220 11 24 12 30 21 18 27 equation for the data of the form bo + b z. Comment on the adequacy of this equation for predicting p. Enter negative value as negative number. x (to 2 decimals) R-sq adj (to 1 decimal) (to 1 decimal) Analysis of Variance SOURCE OF MS F-value (to 2 Residual Error Total |%(to 1 decimal) of the variability in y has been explained byz,...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures where 1inventory investment ($1000s) = advertising expenditures ($1000s) y sales ($1000s) The data used to develop the model came from a survey of 10 stores; for those data, SST 16,000 and SSR a. Compute SSE, MSE, and MSR (to 2 decimals, if necessary) 12,000 SSE MSE MSR b. Use an F test and α .05 level of significance to determine whether there is...