Making Sense of Statistical Significance Key Terms Flashcards
Alpha (α)
Probability of making a Type I error; same as significance level.
Beta (ß)
Probability of making a Type II error.
d:
Effect size =
Decision Errors
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.
Effect Size (d)
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.
Effect Size Conventions
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.
Meta-Analysis
Statistical method for combining effect sizes from different studies.
Power Tables
A table showing the statistical power of a study for various effect sizes and sample sizes
Statistical Power
Probability that the study will give a significant result if the research hypothesis is true.
Type I Error
Rejecting the null hypothesis when in fact it is true; getting a statistically significant result when in fact the research hypothesis is not true.
Type II Error
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.