Significance Tests Review 2024

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What is a hypothesis test?

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A hypothesis test is a statistical method used to make decisions about the validity of a claim based on sample data. It assesses the strength of evidence against a null hypothesis.

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What is the null hypothesis (H0)?

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The null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

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What is the alternative hypothesis (Ha)?

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The alternative hypothesis (Ha) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

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What does a significance level (α) represent in hypothesis testing?

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The significance level (α) is the probability of rejecting the null hypothesis when it is actually true, commonly set at 0.05.

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What is a p-value?

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

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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 from the sample data is strong enough to conclude that the null hypothesis is unlikely to be true.

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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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How do you determine the appropriate hypotheses for a claim?

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To determine the appropriate hypotheses, identify the claim being tested and formulate the null hypothesis as a statement of equality, while the alternative hypothesis reflects the claim.

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What is the formula for calculating the test statistic for a proportion?

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The test statistic for a proportion is calculated using the formula: z = (p̂ - p0) / √(p0(1 - p0) / n), where p̂ is the sample proportion, p0 is the hypothesized proportion, and n is the sample size.