Question

A researcher sets alpha=.05 and conducts a study to compare two groups. If there truly is no difference in the population means, what is the probability of a Type I error?

1) .00
2) .01
3) .05
4) .20

Answer 1

The probability of making a Type I error when the alpha level is set at 0.05 is 5%. This means if there is no actual difference in the population means, there's a 5% chance of incorrectly rejecting the true null hypothesis.

Step-by-step explanation:

When a researcher sets an alpha level at 0.05, they are specifying the threshold for making a decision about the null hypothesis. In this case, alpha represents the probability of making a Type I error, which occurs when the researcher rejects a true null hypothesis. Since the alpha level is set at 0.05, if there truly is no difference in the population means, the probability of making a Type I error is 0.05 or 5%.

A Type I error is often referred to as a 'false positive', and it is a risk that researchers accept when setting an alpha level. Stating it simply, there is a 5% chance that the researcher will find evidence of a difference between groups when no such difference actually exists.