Significance Tests

Front

What is a p-value in the context of significance tests?

Back

A p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

Front

What does it mean to 'reject the null hypothesis'?

Back

Rejecting the null hypothesis means that there is sufficient evidence to support the alternative hypothesis.

Front

What is the significance level (α) in hypothesis testing?

Back

The significance level (α) is the threshold for determining whether a p-value indicates significant evidence against the null hypothesis, commonly set at 0.05.

Front

What are the null and alternative hypotheses?

Back

The null hypothesis (H0) is a statement of no effect or no difference, while the alternative hypothesis (Ha) represents the statement we want to test for evidence against H0.

Front

What does a small p-value indicate?

Back

A small p-value (typically < 0.05) indicates strong evidence against the null hypothesis, suggesting that it may be rejected.

Front

What is the conclusion if p-value < α?

Back

If the p-value is less than the significance level (α), we reject the null hypothesis.

Front

What is the conclusion if p-value > α?

Back

If the p-value is greater than the significance level (α), we fail to reject the null hypothesis.

Front

What is a Type I error?

Back

A Type I error occurs when the null hypothesis is true but is incorrectly rejected.

Front

What is a Type II error?

Back

A Type II error occurs when the null hypothesis is false but fails to be rejected.

Front

What does 'statistically significant' mean?

Back

Statistically significant means that the results observed in the data are unlikely to have occurred under the null hypothesis, typically indicated by a p-value less than α.