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Power: The probability that you would identify a true effect of the independent variable.

Power: The probability that you would identify a true effect of the independent variable. Type Two error: Labeling an outcome as related to random events when it actually is because of the independent variable. Type Two error: Accepting the null hypothesis when it is false.  error

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Power: The probability that you would identify a true effect of the independent variable.

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  1. Power: The probability that you would identify a true effect of the independent variable.

  2. Type Two error: Labeling an outcome as related to random events when it actually is because of the independent variable.

  3. Type Two error: Accepting the null hypothesis when it is false.

  4.  error Where  represents the probability that this type of error would occur.

  5. Ho :  = 50 H1:  > 50  = .05 50 o

  6. 0 1  

  7. Power = 1 -  0 1  

  8. Three things can effect power. 1) The level of significance

  9.  gets smaller  gets bigger

  10. 2) Increase the sample size (N)

  11. Larger N - smaller standard error Therefore less overlap of the distributions

  12. 3) Increase the distance from 0 to  1

  13. 0 1  

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