6 Hypothesis Testing Free Online FlashCards

What does hypothesis testing assess?

It uses sample data to assess whether they are sufficiently inconsistent with a specified null hypothesis about a population.

What does the null hypothesis represent?

The null hypothesis, written as $H_0$, is the benchmark or no-effect claim being evaluated.

What does the alternative hypothesis express?

The alternative hypothesis, written as $H_a$ or $H_1$, expresses the effect or difference being investigated.

What should hypotheses describe?

Both hypotheses are statements about a population parameter, such as a mean, proportion, or difference between groups.

Where does equality belong in a hypothesis test?

The equality belongs in the null hypothesis. For example, a benchmark mean of 4 minutes can be written $H_0: \mu = 4$.

How do one-sided and two-sided alternatives differ?

A one-sided alternative specifies a direction, such as $H_a: \mu < 4$; a two-sided alternative tests for any difference, such as $H_a: \mu \ne 4$.

When should a test's direction be chosen?

Choose the direction before examining results, based on the research question and the consequences of possible errors.

What does a p-value measure?

Assuming the null hypothesis and test assumptions are true, it is the probability of observing a test statistic at least as extreme as the one obtained, in the direction or directions specified by the alternative.

Is a p-value the probability that the null hypothesis is true?

No. A p-value is calculated assuming the null hypothesis is true; it is not the probability that the null hypothesis is true.

How is a p-value compared with the significance level?

Reject $H_0$ when $p \leq \alpha$; otherwise, fail to reject $H_0$.

What does the significance level $\alpha$ control?

The significance level $\alpha$ is the chosen maximum probability of a Type I error under the null hypothesis.

What are Type I and Type II errors?

A Type I error rejects a true null hypothesis; a Type II error fails to reject a false null hypothesis. The probability of a Type II error is denoted $\beta$.