Lecture 15 - Non-Parametric Tests Part 2

Question 1

In what situation is a Kruskal-Wallis H test suitable?

Answer 1

When the data is non-parametric, the design is between-groups, there is one IV with multiple levels and the DV is ordinal.

Question 2

What is the rationale behind a Kruskal-Wallis H test?

Answer 2

Distribution of ranks across groups is either random or systematic depending on whether H₁ is true.

Question 3

How is a Kruskal-Wallis H test carried out by hand?

Answer 3

All scores are ranked ignoring the IV.

H is calculated using N, the sum of ranks for each level of the variable (R_i) and the number of scores in each level of the variable (n_i).

Question 4

How is a Kruskal-Wallis H test carried out in SPSS?

Answer 4

Analyse/Non-parametric tests/k independent samples.
Test variable= DV, grouping variable=IV. Define range and check Kruskal-Wallis box.

Question 5

In SPSS, what output is there for a Kruskal-Wallis H test and what is the useful information?

Answer 5

Ranks and Test Statistics.
SPSS converts H into X², and the df and sig. are also useful.

Question 6

What is a problem with Kruskal-Wallis H tests and how can this be corrected for?

Answer 6

They tell us that the conditions differ, but not which ones, so to find this out multiple Mann-Whitney U tests with Bonferroni corrections must be carried out.

Question 7

In what situation should a Friedman test be used?

Answer 7

When the data are non-parametric, the samples are paired (within-subject and matched-subject designs), there is one IV with >2 levels (3+) and the DV is an ordinal scale.

Question 8

What is the rationale behind a Friedman test?

Answer 8

Each individual subject’s scores are ranked (i.e. for three IV levels the ranks are 1-3) and the rank totals for each IV level calculated. If H₀=true, expect random rank distribution and roughly equal totals.

Question 9

How is a Friedman test carried out?

Answer 9

Once the IV level subject ranks have been totalled (R), the test statistic, X²_R, is calculated using N, R and k (no. of IV levels).

Question 10

How do you conduct a Friedman test on SPSS?

Answer 10

Analyse/Nonparametric Tests/k Related Samples
Test variables = IV levels
Check Friedman box.

Question 11

What does the output from a Friedman test in SPSS contain and what information is useful?

Answer 11

Ranks and Test Statistics.
X², df and sig. values are reported.

Question 12

What is a problem with Friedman tests and how can it be solved?

Answer 12

As with Kruskal-Wallis, it doesn’t say which conditions differ. Multiple Bonferroni-corrected Wilcoxon tests can be used to determine this.