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Power and Effect Size

Power and Effect Size. Errors. Type I Rejecting the Null hypothesis when it is true Type II Failing to reject the Null hypothesis when in fact we should. Errors cont. Power. The probability of rejecting H o when H o is false. Factors affecting Power. Alpha ( ).

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Power and Effect Size

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  1. Power and Effect Size

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

  3. Errors cont.

  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

  10. Example from Howell p191 - 195 Effect Size for Matched Samples

  11. Effect Size for Independent Samples

  12. Harmonic mean Unequal Sample sizes

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

  14. 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

  15. Ways of increasing power in a study

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