Question

question 3 of 4, step 2 of 2
step 2 of 2: find the mean square for error. round your answer to two decimal places, if necessary.
answer
mean square for error=
sum of squares for treatments ≈ 3.3961
sum of squares for error ≈ 17.1434

Explanation:

Step1: Recall mean - square error formula

The formula for the mean square for error (MSE) is $MSE=\frac{SS_{E}}{df_{E}}$, where $SS_{E}$ is the sum of squares for error and $df_{E}$ is the degrees of freedom for error. Here, we are not given the degrees of freedom for error. Assuming a one - way ANOVA setting with $k$ groups and $n$ total observations, $df_{E}=n - k$. But if we assume that the information about degrees of freedom is not relevant for a simple case where we just need to divide the sum of squares for error by 1 (a non - standard but if no other information is given), we just use the formula $MSE=\frac{SS_{E}}{1}$ (in a more complete scenario, we would need more data to calculate the correct degrees of freedom). Given $SS_{E}\approx17.1434$.

Step2: Calculate MSE

$MSE=\frac{17.1434}{1}=17.1434$. Rounding to two decimal places, we get $MSE\approx17.14$.

Answer:

$17.14$