Nonparametric tests: Tests without population parameters (means and standard deviations)

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Presentation transcript:

Nonparametric tests: Tests without population parameters (means and standard deviations)

Use when: Data does not support means (ordinal) Data is not normally distributed.

1) Rank all data. 2) Evaluate if ranks tend to cluster within a group.

Mann Whitney U test: nonparametric equivalent of a t test for two independent samples

Mann Whitney U test: Where: Size of sample one Size of sample two

Mann Whitney U test: Where: Sum of sample one ranks Sum of sample two ranks

Evaluation of Mann Whitney U 1) Choose the smaller of the two U values. 2) Find the critical value (Mann Whitney table) 3) When computed value is smaller than the critical value the outcome is significant!

group 1 group

group 1 group Step One: Rank all data across groups

group 1 group

group 1 group

Tied ranks: Find all values that are tied. Identify all ranks that would be assigned to those values. Average those ranks. Assign that average to all tied values.

group 1 group

8th and 9th ranks would be used. 8+9 = 17 Averaging 17/ 2 = 8.5 ranks

group 1 group

group 1 group

group 1 group Step Two: Sum the ranks for each group

Check the rankings:

group 1 group

= 78

Step Three: Compute U 1

Step Four: Compute U 2

Step Five: Compare U 1 to U 2

Critical Value = 5 This is a nonsignificant outcome

group 1 group