Consider the partially completed ANOVA table showing the results of a regression analysis shown.

$\begin{array}{|lcrcl|}
\hline \text { Source of } & {\text { Sum of }} & {\text { Mean }} & \
\text { variation } & \text { squares } & \text { df } & \text { squares } & \text { F-ratio } \
\text { Regression } & 305.1 & 1 & ? & ? \
\text { Residual } & 1247.3 & 24 & ? & \
\text { Total } & 1552.4 & 25 & & \
\hline
\end{array}$
-What is a weakness of the ANOVA method compared to the t-test method when performing a significance test on the slope of a regression?

Question

Consider the partially completed ANOVA table showing the results of a regression analysis shown.
​
 $\begin{array}{|lcrcl|}
\hline \text { Source of } & {\text { Sum of }} & {\text { Mean }} & \
\text { variation } & \text { squares } & \text { df } & \text { squares } & \text { F-ratio } \
\text { Regression } & 305.1 & 1 & ? & ? \
\text { Residual } & 1247.3 & 24 & ? & \
\text { Total } & 1552.4 & 25 & & \
\hline
\end{array}$
-What is a weakness of the ANOVA method compared to the t-test method when performing a significance test on the slope of a regression?

Quizplus · Accepted Answer

ANOVA tests the null hypothesis that the means of two or more groups are equal. It does not directly test against null hypothesis slopes different from 0, which is a specific capability of t-tests in the context of regression analysis. This limitation can be seen as a weakness when the objective is to assess the significance of the slope of a regression line.

Consider the Partially Completed ANOVA Table Showing the Results of a Regression