The following regression model was estimated. Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Exis the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household in each outlet's immediate service area. Least squares estimation of the regression equation on the basis of the 25 data observations resulted in the estimated regression coefficients and other statistics given in Table below. Variable Coefficient Standard Error of Coefficient Intercept 128832,240 69974.818 Price (P) -19875.954 4100.856 Competitor Price (Px) 15467.936 459.280 Advertising (Ad) 0.261 0.094 Income (I) 8.780 1.017 Coefficient of determination R =83.3% (a) Interpret the coefficients of independent variables. (b) Test the significance of independent variables at 5% level of Significance. (c) Interpret R? with the help of adjusted R?. (d) Test for the overall significance of the regression. Explain the nature, causes, consequences and remedial measures of any one data disease (e) (Auto Hetro Multi) if present in the given model.
The following regression model was estimated. Q is the number of meals served, P is the average price per meal (customer ticket amount, in dollars), Exis the average price charged by competitors (in dollars), Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household in each outlet's immediate service area. Least squares estimation of the regression equation on the basis of the 25 data observations resulted in the estimated regression coefficients and other statistics given in Table below. Variable Coefficient Standard Error of Coefficient Intercept 128832,240 69974.818 Price (P) -19875.954 4100.856 Competitor Price (Px) 15467.936 459.280 Advertising (Ad) 0.261 0.094 Income (I) 8.780 1.017 Coefficient of determination R =83.3% (a) Interpret the coefficients of independent variables. (b) Test the significance of independent variables at 5% level of Significance. (c) Interpret R? with the help of adjusted R?. (d) Test for the overall significance of the regression. Explain the nature, causes, consequences and remedial measures of any one data disease (e) (Auto Hetro Multi) if present in the given model.
Chapter4: Linear Functions
Section4.3: Fitting Linear Models To Data
Problem 34SE: For the following exercises, consider this scenario: The profit of a company decreased steadily...
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Transcribed Image Text:The following regression model was estimated. Q is the number of meals served, P is the average price
per meal (customer ticket amount, in dollars), Exis the average price charged by competitors (in dollars),
Ad is the local advertising budget for each outlet (in dollars), and I is the average income per household
in each outlet's immediate service area. Least squares estimation of the regression equation on the basis
of the 25 data observations resulted in the estimated regression coefficients and other statistics given in
Table below.
Variable
Coefficient
Standard Error of Coefficient
Intercept
128832,240
69974.818
Price (P)
-19875.954
4100.856
Competitor Price (Px)
15467.936
459.280
Advertising (Ad)
0.261
0.094
Income (I)
8.780
1.017
Coefficient of determination R =83.3%
(a)
Interpret the coefficients of independent variables.
(b)
Test the significance of independent variables at 5% level of Significance.
(c)
Interpret R? with the help of adjusted R?.
(d)
Test for the overall significance of the regression.
Explain the nature, causes, consequences and remedial measures of any one data disease
(e)
(Auto Hetro Multi) if present in the given model.
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