1. Power and Effect Size

2. Errors Type I Type II Rejecting the Null hypothesis when it is true
Failing to reject the Null hypothesis when in fact we should.

3. Errors cont. True State of the World Decision H0 True H0 False
Reject H0
Type I error
p = α
Correct decision
p = 1 - β = Power
Fail to reject H0
p = 1 - α
Type II error
p = β

4. Power
The probability of rejecting Ho when Ho is false

5. Factors affecting Power
Alpha ()

6. Factors affecting Power
Sample Size

7. Factors affecting Power
Variability of dependent scores
Statistical test

8. Factors affecting Power
The true alternative hypothesis

9. Factors affecting Power
Effect Size
Extent to which the two distributions do not overlap
Cohen

11. Effect Size for Matched Samples
Example from Howell p

12. Effect Size for Independent Samples

13. Unequal Sample sizes
Harmonic mean

14. Power when designing experiments
Cohen
Optimum level of power - .80

15. Estimating Effect Size
based on previous research - can provide a useful estimate.
estimated using the method of mimimum meaningful differences, i.e. the smallest difference that will matter,
Cohen’s effect size conventions - .2, .5, .8
Meta-analysis

16. Ways of increasing power in a study