Null and Alternative Hypotheses

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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 a starting point for statistical 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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How do you formulate a null hypothesis for a mean?

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To formulate a null hypothesis for a mean, you typically state that the population mean (μ) is equal to a specific value (e.g., H0: μ = 2).

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How do you formulate an alternative hypothesis for a mean?

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To formulate an alternative hypothesis for a mean, you state that the population mean (μ) is not equal to, greater than, or less than a specific value (e.g., Ha: μ < 2 or Ha: μ ≠ 18.4).

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What does it mean if the null hypothesis is rejected?

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If the null hypothesis is rejected, it suggests that there is sufficient evidence to support the alternative hypothesis.

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What is a two-tailed hypothesis test?

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A two-tailed hypothesis test is used when the alternative hypothesis states that the parameter is not equal to a specific value (e.g., Ha: μ ≠ 18.4).

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What is a one-tailed hypothesis test?

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A one-tailed hypothesis test is used when the alternative hypothesis states that the parameter is either greater than or less than a specific value (e.g., Ha: μ < 2 or Ha: μ > 30).

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

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The significance level (alpha) 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 Type I error in hypothesis testing?

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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 in hypothesis testing?

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A Type II error occurs when the null hypothesis is not rejected when the alternative hypothesis is true.