Making Sense of Statistical Significance Key Terms

Question 1

Alpha (α)

Answer 1

Probability of making a Type I error; same as significance level.

Question 2

Beta (ß)

Answer 2

Probability of making a Type II error.

Question 3

d:

Answer 3

Effect size =

Question 4

Decision Errors

Answer 4

Incorrect conclusion in hypothesis testing in relation to the real (but unknown) situation, such as deciding the null hypothesis is false when it is really true.

Question 5

Effect Size (d)

Answer 5

Standardized measure of difference (lack of overlap) between populations. Effect size increases with greater differences between means, it is a measure of the difference between population means.

Question 6

Effect Size Conventions

Answer 6

Standard rules about what to consider a small, medium, and large effect size, based what is typical in psychology research; also known as Cohen’s conventions.

Question 7

Meta-Analysis

Answer 7

Statistical method for combining effect sizes from different studies.

Question 8

Power Tables

Answer 8

A table showing the statistical power of a study for various effect sizes and sample sizes

Question 9

Statistical Power

Answer 9

Probability that the study will give a significant result if the research hypothesis is true.

Question 10

Type I Error

Answer 10

Rejecting the null hypothesis when in fact it is true; getting a statistically significant result when in fact the research hypothesis is not true.

Question 11

Type II Error

Answer 11

Failing to reject the null hypothesis when in fact it is false; failing to get a statistically significant result when in fact the research hypothesis is true.