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