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Flashcards in Non-Parametric Alternatives Deck (14)
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1

Assumptions for data to be parametric

-data level of measurement to be continuous
-normally distributed
-equal variances across groups to compare

2

Which non-parametric test would you use in the place of the Student's t test?

Mann-Whitney U test

3

Which non-parametric test would you use in the place of the paired t-test?

Wilcoxon signed-rank test

4

Which non-parametric test would you use in the place of ANOVA?

Kruskal-Wallis H test

5

Which non-parametric test would you use in the place of repeated measures ANOVA?

Friedman test

6

How are the scores ordered in non-parametric rankings?

scores are ranked from smallest to largest with 1 assigned to the smallest score and n to the highest score

7

T/F: non-parametric tests make no assumption on the distribution of data

True

8

What are 2 reasons non-parametric tests may not be testing the null hypothesis of interest

null hypotheses that can be studied using non-parametric tests tend to be very restrictive

there is not much choice for non-parametric tests

9

T/F Non-parametric methods are focused on estimation rather than significance testing

False: more focused on significance

Non-parametric tests can't calculate CI

10

Mann-Whitney U test

used to test mean difference between two independent groups

11

Wilcoxon Signed-Rank Test

used to test mean difference between two matched groups

12

Kruskal-Wallis H test

used to test mean difference between 3 or more independent groups

13

Friedman test

used to test the mean difference between 3 or more related groups

14

List the weaknesses of non-parametric tests

less powerful than parametric

may not be testing null hypothesis of interest

null hypotheses using non parametric tests tend to be restrictive

not much choice

can't be related to the CI