Multiple Choice
When conducting a significance test in practice, how should you choose the level?
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9. Hypothesis Testing for One Sample
Steps in Hypothesis Testing
Multiple Choice
Which of the following correctly describes the steps for testing a hypothesis using the -value approach, including verifying the requirements of the test?
A
Calculate the -value, state the null hypothesis, verify the requirements, and then always reject the null hypothesis if the -value is less than .
B
Verify the requirements, state the alternative hypothesis only, calculate the test statistic, and accept the null hypothesis if the -value is greater than the significance level.
C
State the hypotheses, skip verifying requirements, calculate the -value, and always accept the alternative hypothesis if the -value is less than the significance level.
D
State the null and alternative hypotheses, verify the requirements of the test, calculate the test statistic and -value, compare the -value to the significance level, and make a decision to reject or fail to reject the null hypothesis.
Verified step by step guidance1
Step 1: State the null hypothesis (\(H_0\)) and the alternative hypothesis (\(H_a\)). The null hypothesis usually represents the status quo or no effect, while the alternative represents what you want to test for.
Step 2: Verify the requirements or assumptions of the test. This may include checking conditions such as sample size, normality, independence, or equal variances, depending on the test being used.
Step 3: Calculate the test statistic based on your sample data. The test statistic measures how far your sample data deviates from what is expected under the null hypothesis.
Step 4: Calculate the p-value, which is the probability of observing a test statistic as extreme as, or more extreme than, the one calculated, assuming the null hypothesis is true.
Step 5: Compare the p-value to the significance level (\(\alpha\)). If the p-value is less than or equal to \(\alpha\), reject the null hypothesis; otherwise, fail to reject the null hypothesis.
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