Lecture Notes on Statistical Significance and Error Types

Flashcards covering key vocabulary related to statistical significance and error types in hypothesis testing.

Alpha

The probability level that researchers set to determine statistical significance; often set at 0.05, meaning results are significant if the probability of them happening by chance is less than 5%.

Type I Error

The error of concluding that a difference exists when, in fact, it does not; also known as a 'false positive'.

Type II Error

The error of concluding that there is no difference when, in fact, there is a difference; also known as a 'false negative'.

P-value

The probability of making a Type I error; indicates whether the results are statistically significant (not due only to chance).

Statistical Significance

When the probability of results happening by chance is less than the set alpha level (e.g., 0.05).