How can we decide whether our group means are significantly different in an ANOVA?

If any group differs significantly from the overall group mean, then the ANOVA will report a statistically significant result. If the F statistic is higher than the critical value (the value of F that corresponds with your alpha value, usually 0.05), then the difference among groups is deemed statistically significant.

Does an ANOVA test identify specifically where the differences exist between the groups?

It determines whether all the samples are the same. The one-way ANOVA is used to determine whether there are any statistically significant differences between the means of three or more independent (unrelated) groups.

What if there is no significant difference in ANOVA?

Surprisingly, the answer is yes. With one exception, post tests are valid even if the overall ANOVA did not find a significant difference among means. The exception is the first multiple comparison test invented, the protected Fisher Least Significant Difference (LSD) test.

How many groups can you compare with ANOVA?

A one-way ANOVA compares three or more than three categorical groups to establish whether there is a difference between them. Within each group there should be three or more observations (here, this means walruses), and the means of the samples are compared.

Why is ANOVA better than multiple t tests?

Two-way anova would be better than multiple t-tests for two reasons: (a) the within-cell variation will likely be smaller in the two-way design (since the t-test ignores the 2nd factor and interaction as sources of variation for the DV); and (b) the two-way design allows for test of interaction of the two factors ( …

How do you know if one-way ANOVA is significant?

Interpretation. Use the p-value in the ANOVA output to determine whether the differences between some of the means are statistically significant. To determine whether any of the differences between the means are statistically significant, compare the p-value to your significance level to assess the null hypothesis.

Can ANOVA be used for 2 groups?

Typically, a one-way ANOVA is used when you have three or more categorical, independent groups, but it can be used for just two groups (but an independent-samples t-test is more commonly used for two groups).

Why is ANOVA significant but post hoc test not?

You can get misleading results from ANOVA in various situations. The post hoc tests focus on differences between groups they have more power to detect such differences even though the overall ANOVA indicates that the differences among the means are not statistically significant.

What would happen if instead of using an ANOVA to compare 10 groups you perform multiple t tests?

What would happen if instead of using an ANOVA to compare 10 groups, you performed multiple t- tests? a. Nothing, there is no difference between using an ANOVA and using a t-test. Making multiple comparisons with a t-test increases the probability of making a Type I error.

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.

Can we use ANOVA in comparing 2 groups Why?

For a comparison of more than two group means the one-way analysis of variance (ANOVA) is the appropriate method instead of the t test. The ANOVA method assesses the relative size of variance among group means (between group variance) compared to the average variance within groups (within group variance).