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 (H1)?

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The alternative hypothesis (H1) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

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What does it mean if H0: μ = 47 and H1: μ < 47?

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This means we are testing whether the true mean mileage of the cars is less than 47 mpg, suggesting the manufacturer's claim may be overstated.

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What is a one-tailed test?

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A one-tailed test is a hypothesis test that evaluates whether a parameter is either greater than or less than a certain value, but not both.

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What is a two-tailed test?

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A two-tailed test is a hypothesis test that evaluates whether a parameter is different from a certain value, considering both directions (greater than and less than).

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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 is the significance level (α)?

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The significance level (α) is the probability of making a Type I error, commonly set at 0.05 or 0.01.

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What does p-value represent in hypothesis testing?

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

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What is the purpose of hypothesis testing?

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The purpose of hypothesis testing is to make inferences about population parameters based on sample data.