Set up the ANOVA table in the manner of Table 5.4 for the regression model given in Eq. (3.7.2) and test the hypothesis that there is no relationship between food expenditure and total expenditure in India.> $\begin{aligned} \widehat{\text { FoodExp }_{i}} &=94.2087+0.4368 \text { Totalexp }_{i} & \\ \operatorname{var}\left(\hat{\beta}_{1}\right) &=2560.9401 & & \operatorname{se}\left(\hat{\beta}_{1}\right)=50.8563 \\ \operatorname{var}\left(\hat{\beta}_{2}\right) &=0.0061 & & \operatorname{se}\left(\hat{\beta}_{2}\right) \\ r^{2} &=0.3698 & \hat{\sigma}^{2} &=4469.6913 \end{aligned}$
Set up the ANOVA table in the manner of Table 5.4 for the regression model given in Eq. (3.7.2) and test the hypothesis that there is no relationship between food expenditure and total expenditure in India.
$\begin{array}{rlrl}\widehat{\text { FoodExp }}_{i} & =94.2087+0.4368 \text { TotalExp }_{i} \\ \operatorname{var}\left(\hat{\beta}_{1}\right) & =2560.9401 & \operatorname{se}\left(\hat{\beta}_{1}\right) & =50.8563 \\ \operatorname{var}\left(\hat{\beta}_{2}\right) & =0.0061 & \operatorname{se}\left(\hat{\beta}_{2}\right) & =0.0783 \\ r^{2} & =0.3698 & \hat{\sigma}^{2} & =4469.6913\end{array}$
TABLE 5.4 ANOVA Table for the Wages-Education Example