- Understand what is measured by SSRegression, SSResiduals, and SSTotal in a regression context
- Discuss the factors that affect the value of F-statistics in a regression context
The ANOVA table will also include a P-value, which tells the probability of obtaining an F-statistic as large or larger than the one in the sample if the null hypothesis was true.
An ANOVA F-test can be used to test the population slope for simple linear regression, the same scenario where you used a t-test.
To model the values of the F-statistic that would occur if the null hypothesis was true and the assumptions for inference were met, you will use an F Distribution with [latex]df_1 = p[/latex] and [latex]df_2 = n-1-p[/latex].
Step 2: Enter the df1 and df2 accordingly
Step 3: For the “Type of Probability” select “Upper Tail”.
Step 4: Enter the [latex]F[/latex] value as the value of [latex]x[/latex]
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Suppose you had conducted a t-test for the slope instead of an F-test for the slope in this scenario. The value of the t-statistic would have been [latex]7.50[/latex], the square root of the F-statistic. The P-value for the two-sided t-test would be the same as the P-value for the F-test.