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Can you do Chi square with more than two categories?
Chi-square can also be used with more than two categories. For instance, we might examine gender and political affiliation with 3 categories for political affiliation (Democrat, Republican, and Independent) or 4 categories (Democratic, Republican, Independent, and Green Party).
Why is multiple testing bad?
If researchers look at enough characteristics of a given sample, they are bound to discover these quirks and conclude (mistakenly) that they have significance for the whole population. This is the problem of multiple testing—the more tests you run on a sample, the greater the likelihood of a chance finding.
When do you not use multiple comparisons?
Here are three situations were special calculations are not needed.
- Account for multiple comparisons when interpreting the results rather than in the calculations.
- Corrections for multiple comparisons may not be needed if you make only a few planned comparisons.
When do you not do multiple test corrections?
Some statisticians recommend never correcting for multiple comparisons while analyzing data (1,2). Instead report all of the individual P values and confidence intervals, and make it clear that no mathematical correction was made for multiple comparisons. This approach requires that all comparisons be reported.
Is there a way to test for independence of observations?
There is no way to test for independence of observations. This assumption can only be satisfied by correctly randomising your experimental design. Bartlett’s test tests the null hypothesis that the group variances are equal against the alternative hypothesis that the group variances are not equal.
How are the data independent of each other?
The data (scores) are independent of each other (that is, scores of one participant are not systematically related to scores of the other participants). This is commonly referred to as the assumption of independence. The test (dependent) variable is normally distributed within each of the two populations (as defined by the grouping variable).
How can one way ANOVA be used to test independence?
There is no way to use the study’s data to test whether independence has been achieved; rather, independence is achieved by correctly randomising sample selection. If the observations are not independent, then the one-way ANOVA is an inappropriate statistic.
When is the chi square test of Independence not appropriate?
If your categorical variables represent “pre-test” and “post-test” observations, then the chi-square test of independence is not appropriate. This is because the assumption of the independence of observations is violated.