Significance Tests

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What is a significance test?

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A significance test is a statistical method used to determine if there is enough evidence to reject a null hypothesis in favor of an alternative hypothesis.

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What are the null and alternative hypotheses?

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The null hypothesis (H0) is a statement that there is no effect or no difference, while the alternative hypothesis (Ha) is what you want to prove, indicating that there is an effect or a difference.

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What is a Type I error?

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A Type I error occurs when the null hypothesis is rejected when it is actually true.

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What is a Type II error?

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A Type II error occurs when the null hypothesis is not rejected when it is actually false.

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What does a p-value represent?

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

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What is the significance level (alpha)?

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The significance level (alpha) is the threshold for rejecting the null hypothesis, commonly set at 0.05 or 0.01.

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What does it mean to reject the null hypothesis?

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Rejecting the null hypothesis means that the evidence suggests that the alternative hypothesis is true.

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

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Failing to reject the null hypothesis means that there is not enough evidence to support the alternative hypothesis.

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What is the difference between one-tailed and two-tailed tests?

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A one-tailed test checks for the possibility of the relationship in one direction, while a two-tailed test checks for the possibility in both directions.

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What is a confidence interval?

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A confidence interval is a range of values that is likely to contain the population parameter with a certain level of confidence.