Question: Consider this regression output table and residual plot. SUMMARY OUTPUT Dependent Variable: Total Sales ($) Regression Statistics Multiple R 0.7033 R square 0.4946 Adjusted R

Consider this regression output table and residual plot. SUMMARY OUTPUT Dependent Variable: Total Sales ($) Regression Statistics Multiple R 0.7033 R square 0.4946 Adjusted R Square 0.4858 Standard Error 392.21 Observations 60 ANOVA df SS MS F Significance f Regression 1 8.73E+06 8.73E+06 56.75 0.0000 Residual 58 8.92E+06 1.54E+05 Total 59 1.77E+07 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -781.47 315.22 -2.48 0.0161 -1,412.46 -150.48 High Temperature (in degrees F) 64.19 8.52 7.53 0.0000 47.13 81.24 Residual plot for the variable High Temperature Access image details Which of the following statements regarding the regression analysis is NOT true? There is a significant linear relationship between the dependent and independent variables. The linear model may not be the best fit for the relationship. The independent variable explains 48.58% of the variation in the dependent variable. The best fit line indicates a positive relationship between the dependent and independent variables

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