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), Rxis 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) Competitor Price (Px) | Advertising (Ad) Income () -19875.954 4100.856 15467.936 459.280 0.261 0.094 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 R2. (d) Test for the overall significance of the regression. (e) Explain the nature, causes, consequences and remedial measures of any one data disease (Auto Hetro Multi) if present in the given model.

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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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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), Rxis 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)
Competitor Price (Px)
| Advertising (Ad)
Income ()
-19875.954
4100.856
15467.936
459.280
0.261
0.094
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 R2.
(d) Test for the overall significance of the regression.
(e)
Explain the nature, causes, consequences and remedial measures of any one data disease
(Auto Hetro Multi) if present in the given model.
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), Rxis 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) Competitor Price (Px) | Advertising (Ad) Income () -19875.954 4100.856 15467.936 459.280 0.261 0.094 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 R2. (d) Test for the overall significance of the regression. (e) Explain the nature, causes, consequences and remedial measures of any one data disease (Auto Hetro Multi) if present in the given model.
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