What is Power Analysis?

Power Analysis is an important aspect of experimental design. It allows us to determine the sample size required to detect an effect of a given size with a given degree of confidence.
There are four parameters involved in a power analysis.  The research must ‘know’ 3 and solve
for the 4th.
1. Alpha:   
 Probability of finding significance where there is none  
 False positive  
 Probability of a Type I error   
 Usually set to.05  
2. Power    
 Probability of finding true significance  
 True positive  
 1 – beta, where beta is:  
 Probability of not finding significance when it is there  
 False negative  
 Probability of a Type II error  
 Usually set to.80  
3. N:  
 The sample size (usually the parameter you are solving for)  
 May be known and fixed due to study constraints  
4. Effect size:  
 Usually, the ‘expected effect’ is ascertained from:  
 Pilot study results  
 Published findings from a similar study or studies  
 May need to be calculated from results if not reported  
 May need to be translated as design specific using rules of thumb  
 Field defined ‘meaningful effect’  
 Educated guess (based on informal observations and knowledge of the