Introduction to Hypothesis Testing

These flashcards cover key vocabulary and concepts related to hypothesis testing and inferential statistics.

Inferential Statistics

Statistics used to make inferences about a population based on sample data.

Sampling Error

The difference between the sample statistic and the actual population parameter it estimates.

Null Hypothesis (H0)

The hypothesis that assumes no effect or no difference in the population.

Alternative Hypothesis (Ha)

The hypothesis that states there is a significant effect or difference in the population.

Type I Error

The error of rejecting the null hypothesis when it is actually true.

Type II Error

The error of failing to reject the null hypothesis when it is actually false.

Two-Tailed Test

A hypothesis test that evaluates whether a sample mean is significantly different from a population mean in either direction.

One-Tailed Test

A hypothesis test that evaluates whether a sample mean is significantly greater than or less than a population mean.

Critical Value (z-crit)

The threshold value that determines the boundary of the region of rejection in hypothesis testing.

Power of a Test

The probability that a hypothesis test will correctly reject a false null hypothesis.