What if F is less than F critical?
What if F is less than F critical?
In hypothesis testing, a critical value is a point on the test distribution compares to the test statistic to determine whether to reject the null hypothesis. Since f cal value is less than f critical value and it is in the rejection region. Hence we reject the null hypothesis at 95% confidence level.
What does it mean if test statistic is less than critical value?
If the test statistic is not as extreme as the critical value, then the null hypothesis is not rejected. If the test statistic is less extreme than the critical value, do not reject the null hypothesis.
Is F stat is greater than critical value?
The F critical value is a specific value you compare your f-value to. In general, if your calculated F value in a test is larger than your F critical value, you can reject the null hypothesis. However, the statistic is only one measure of significance in an F Test.
What does a low F statistic mean?
The low F-value graph shows a case where the group means are close together (low variability) relative to the variability within each group. The high F-value graph shows a case where the variability of group means is large relative to the within group variability.
What is the critical F value?
Critical F: The value of the F-statistic at the threshold probability α of mistakenly rejecting a true null hypothesis (the critical Type-I error).
What if p-value is less than alpha?
If your p-value is less than your selected alpha level (typically 0.05), you reject the null hypothesis in favor of the alternative hypothesis. If the p-value is above your alpha value, you fail to reject the null hypothesis.
What would an F value of 1.0 indicate?
If the null hypothesis is true, you expect F to have a value close to 1.0 most of the time. A large F ratio means that the variation among group means is more than you’d expect to see by chance.
What does an F statistic of 1 mean?
The F-distribution is used to quantify this likelihood for differing sample sizes and the confidence or significance we would like the answer to hold. A value of F=1 means that no matter what significance level we use for the test, we will conclude that the two variances are equal.