In a Single-Factor Analysis of Variance, MST Is the Mean

Short Answer

In a single-factor analysis of variance, MST is the mean square for treatments and MSE is the mean square for error. The null hypothesis of equal population means is likely false if: $\begin{array}{|l|l|}\hline \text { A. } & \text { MST is much larger than MSE. } \\\hline \text { B. } & \text { MST is much smaller than MSE. } \\\hline \text { C. } & \text { MST is equal to MSE. } \\\hline \text { D. } & \text { MST is zero. } \\\hline\end{array}$