Testing Hypotheses About Proportions

These flashcards cover key terms and definitions related to testing hypotheses about proportions.

Null Hypothesis (H0)

The hypothesis that states what is generally believed to be the true population parameter, often a statement of 'no effect'.

Alternative Hypothesis (HA)

Also known as the research hypothesis, it is what we want to support to reject the null hypothesis.

P-value

The probability of observing a test statistic this extreme or more extreme if the null hypothesis is true.

Significance Level (α)

The pre-specified probability threshold for deciding when to reject the null hypothesis.

Type I Error

Occurs when the null hypothesis is true, but we mistakenly reject it.

Type II Error

Occurs when the null hypothesis is false, but we fail to reject it.

Test Statistic

A sample statistic computed from the data to help make a statistical decision.

Power of the test

The probability of correctly rejecting a false null hypothesis, defined as 1 - Type II error.

Confidence Interval

A range of values used to estimate the true population parameter with a certain level of confidence.

Practical Significance

The importance of a result in the real world, beyond statistical significance.