Hypothesis Testing

Hypothesis Testing

A statistical method used to decide whether a parameter equals the value stated in a null hypothesis based on data.

Null Hypothesis (H0)

A specific claim about a parameter that is assumed to be true unless evidence suggests otherwise.

Alternative Hypothesis (HA)

The hypothesis that includes all values for the parameter other than those stated in the null hypothesis.

Test Statistic

A quantity calculated from data to evaluate how compatible the data are with the null hypothesis.

Null Distribution

The sampling distribution of the test statistic under the assumption that the null hypothesis is true.

P-value

The probability of obtaining a difference from the null expectation as great as or greater than that observed in the data if the null hypothesis were true.

Significance Level (α)

The threshold that determines when to reject the null hypothesis, typically set at 0.05.

Type I Error

The error made when rejecting a true null hypothesis.

Type II Error

The error made when failing to reject a false null hypothesis.

Power of a Test

The probability that a random sample leads to rejection of a false null hypothesis.

Sample Size

Increasing this can increase the power of a test.

Two-Sided Test

A hypothesis test where the alternative hypothesis includes parameter values on both sides of the null hypothesis value.

One-Sided Test

A hypothesis test where the alternative hypothesis includes parameter values on only one side of the null hypothesis value.

Confidence Interval

A range of values that should accompany the results of a hypothesis test to provide bounds on the magnitude of effect.