F-Critical Value
The F test is commonly used to compare differences between two samples. The test statistic thus obtained is also used for regression analysis. The critical value of f is given as:
Find the alpha level
- Subtract 1 from the size of the original sample. This gives them the first freedom. Say, x.
- Similarly, subtract 1 from the second sample size to obtain the second df. Say, y.
- f Using the distribution x and row y, the distribution table will produce a critical value of f.
Test Statistic for large samples: f = [Tex]\sigma[/Tex]12 / [Tex]\sigma[/Tex]22. [Tex]\sigma[/Tex] 12 variance of the first sample and [Tex]\sigma[/Tex] 22 variance of the second sample.
Test Statistic for small samples: f = s12 / s22. S11 variance of the first sample and S22 variance of the second sample.
Critical Value
Critical value is a cut-off value used to mark the beginning of a region where the test statistic obtained in the theoretical test is unlikely to fail. Compared to the obtained test statistic to determine the critical value at hypothesis testing, Null hypothesis is rejected or not. Graphically, the critical value divides the graph into an accepted and rejected region for hypothesis testing. It helps to check the statistical significance of the test statistics. So, critical values are simply the function’s output at these critical points.
In this article, we will learn more about the critical value, its formula, types, and how to calculate its value.
Table of Content
- What is Critical Value?
- Critical Value Formula
- T-Critical Value
- Z-Critical Value
- F-Critical Value
- Chi-Square Critical Value