Hypothesis Testing

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What is hypothesis testing?

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Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (Ha), then using sample data to determine whether to reject H0.

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What is a 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 an alternative hypothesis (Ha)?

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The alternative hypothesis (Ha) is a statement that indicates the presence of an effect or a difference. It is what the researcher aims to support.

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What distribution is used for hypothesis testing about population proportions?

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The z-distribution is used for hypothesis testing about population proportions when the sample size is large enough.

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What is a p-value?

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A p-value is 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 does a low p-value indicate?

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A low p-value (typically less than 0.05) indicates strong evidence against the null hypothesis, leading to its rejection.

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What is a right-tailed test?

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A right-tailed test is a hypothesis test where the alternative hypothesis states that the parameter is greater than a certain value (Ha: µ > k).

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What is a left-tailed test?

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A left-tailed test is a hypothesis test where the alternative hypothesis states that the parameter is less than a certain value (Ha: µ < k).

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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 states that the parameter is not equal to a certain value (Ha: µ ≠ k).

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How do you determine the significance level (α)?

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The significance level (α) is the threshold for rejecting the null hypothesis, commonly set at 0.05, 0.01, or 0.10.