Question

I ran a G*Power analysis to calculate sample size as noted in the chart below: Question 1. What is the interpretive analysis of this data? Question 2. Explain the relationships among effect size, alpha, power and sample size?

Tail	One	Two	Two
Effect Size	0.15	0.15	0.3
a err prob	0.05	0.05	0.1
Power	0.95	0.95	0.99
# Predictors	2	2	2
Sample Size	74	89	55

Answer 1

1. This analysis show that effect size is increased to power of the test because it includes less number of sample size as we consider for smaller effect size and alpha.

2. As we known that there is a relationships among effect size, alpha, power and sample size

power is proportional to sample size and inversely proportional to effect size and alpha.

In this results, we see that sample size decreased as power is increased. This show false result.

Power = 1- alpha

Similarly result are obtained by interchange the form of relationship.