Hypothesis Testing and Statistical (Extra Credit)

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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 right-tailed test indicate?

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A right-tailed test indicates that the alternative hypothesis (Ha) is testing for values greater than a certain threshold.

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What is the significance level (α) 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 or 0.01.

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What is a critical value in hypothesis testing?

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A critical value is a threshold that separates the critical region (where we reject the null hypothesis) from the noncritical region (where we fail to reject the null hypothesis).

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

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To reject the null hypothesis means that the evidence suggests that the alternative hypothesis is true, based on the sample data.

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

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

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What is a two-tailed test?

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A two-tailed test is a hypothesis test where the alternative hypothesis (Ha) tests for values that are either greater than or less than a certain threshold.

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What is a p-value in hypothesis testing?

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The 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 is the difference between Type I and Type II errors?

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Type I error occurs when the null hypothesis is rejected when it is true, while Type II error occurs when the null hypothesis is not rejected when it is false.