What Does Rejecting the Null in ANOVA but Not Hartley's FMAX Mean?

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In summary, ANOVA and Hartley tests serve different purposes - the former compares means while the latter compares variances. Rejecting the null in ANOVA indicates a significant difference in means between groups, while failing to reject Hartley means the variances are assumed to be similar. Additionally, ANOVA is a generalized t-test that can be used for more than 2 groups, while a t-test specifically compares two means using a t-distribution.
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melissahalliwel
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What does it mean when I reject the null in an ANOVA but fail to reject the null when doing something such as Hartleys FMAX?

Also, what's the difference between ANOVA AND T-TEST?
 
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melissahalliwel said:
What does it mean when I reject the null in an ANOVA but fail to reject the null when doing something such as Hartleys FMAX?

Hi melissahalliwel, welcome to MHB!

ANOVA and Hartley test for different things.
The ANOVA tests whether the means of several groups are the same.
Hartley tests if the variances of the groups are similar.

Rejecting the null in ANOVA means there is a group with a different mean.
Failing to reject Hartley means that the variances of the groups are assumed to be similar (even if their means are not).

melissahalliwel said:
Also, what's the difference between ANOVA AND T-TEST?

A textbook will list a whole set of characteristics for each of them.
Anyway, let me try to put some of it in just a couple sentences.

A t-test compares two means.
An ANOVA compares variances. ANOVA is also considered a generalized t-test, as we use it when we have more than 2 groups.

A t-test compares the means directly using a t-distribution.
An ANOVA is an ANalysis of VAriances, meaning it compares variances using an F-distribution.
 

FAQ: What Does Rejecting the Null in ANOVA but Not Hartley's FMAX Mean?

What is the null hypothesis in ANOVA?

The null hypothesis in ANOVA is that there is no significant difference between the means of the groups being compared. In other words, there is no effect of the independent variable on the dependent variable.

How do you reject the null hypothesis in ANOVA?

The null hypothesis is rejected in ANOVA when the calculated F-statistic is greater than the critical value at a given alpha level. This means that the probability of obtaining the observed difference between the group means by chance is less than the chosen alpha level.

What does it mean to reject the null hypothesis in ANOVA?

Rejecting the null hypothesis in ANOVA means that there is a significant difference between the means of the groups being compared. This suggests that the independent variable has an effect on the dependent variable.

Can you reject the null hypothesis in ANOVA without a significant F-statistic?

No, the F-statistic is used to determine whether the null hypothesis can be rejected in ANOVA. If the F-statistic is not significant, then the null hypothesis cannot be rejected and there is no evidence of a significant difference between the group means.

Is rejecting the null hypothesis in ANOVA always meaningful?

Rejecting the null hypothesis in ANOVA is only meaningful if the study has been designed properly and the assumptions of ANOVA have been met. Otherwise, the results may not accurately reflect the true differences between the groups and the null hypothesis may be rejected erroneously.

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