Chapter 6 talks about effect size and statistical power. What are these? How are they relevant to statistics and how do you use them? Since it is talking about effect size do you always want big or do sometimes you want a small or medium? How do you determine this? You can discuss and explain these topics by explaining what are the two factors that determine effect size? For each of these factors, how and why do they effect power?
Effect size is a numerical measure of expressing the strength of relationship between two variables.
The formula for effect size based on means is
Where µ1 is the mean of population 1
µ2 is the mean of population 2
σ is the standard deviation either of the second population or the polled standard deviation of two groups.
Power = probability of rejecting H0 when H0 is false (i.e., you [correctly] conclude that there is a treatment effect when there really is a treatment effect).
Power = 1 − β.
When statistical power increases the chance of type two error decreases
Statistical power depends on
• The structure of the experiment
• The method for analyzing the ...
The effect size and statistical power are defined. How relevant to statistics and how to use them are determined.