How do I know if my ANOVA results are significant?

In ANOVA, the null hypothesis is that there is no difference among group means. If any group differs significantly from the overall group mean, then the ANOVA will report a statistically significant result.

Why is t-test significant but not ANOVA?

What are they? The t-test is a method that determines whether two populations are statistically different from each other, whereas ANOVA determines whether three or more populations are statistically different from each other.

What if t-test is significant?

If you are working with a two-tailed T-Test, double the P-value. Interpret the results. If the result is greater than α, fail to reject the null hypothesis. If you reject the null hypothesis, this implies that your alternative hypothesis is correct, and that the data is significant.

Is it possible for ANOVA to be significant but post hoc test not?

It is possible for an ANOVA test to be significant while the post hoc test is not significant. If the Tukey test was not significant, try another post hoc test like Duncan multiple range test.

What should be done if the ANOVA results show that there is no significant difference between the groups being compared?

If you had a more complex structure and the entire ANOVA showed non-significant differences, then you would make an omnibus conclusion that you did not detect any differences. You would use a post hoc (after the fact) test only if one or more sources of variance was significant.

How do you interpret a significant difference?

In principle, a statistically significant result (usually a difference) is a result that’s not attributed to chance. More technically, it means that if the Null Hypothesis is true (which means there really is no difference), there’s a low probability of getting a result that large or larger.

Why is ANOVA more powerful than T test?

Why not compare groups with multiple t-tests? Every time you conduct a t-test there is a chance that you will make a Type I error. An ANOVA controls for these errors so that the Type I error remains at 5\% and you can be more confident that any statistically significant result you find is not just running lots of tests.

Should I use ANOVA or t test?

If your independent variable has three or more categories, then you must use the ANOVA. The t-test only permits independent variables with only two levels.

Is the T value significant at the 0.05 level and why?

Because the t-value is lower than the critical value on the t-table, we fail to reject the null hypothesis that the sample mean and population mean are statistically different at the 0.05 significance level.

What is a significant difference in at test?

The T-test is a test of a statistical significant difference between two groups. A “significant difference” means that the results that are seen are most likely not due to chance or sampling error.

Is it possible to get a significant result from your F test but then not find significant differences in your post hoc tests?

There is only one special case where this “clustering” won’t distroy the control of the FWER, namely when you have exactely 3 groups (or 3 post-hoc tests) (so this is the case where Fisher’s LSD really controls the FWER).

What if post hoc test is not significant?

If this test is not significant, there is no evidence in the data to reject the null and one then concludes that there is no evidence to suggest that the group means are different. Otherwise, post-hoc tests are performed to find sources of difference.