Hypothesis Testing Flashcards
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Read the first 7 Hypothesis Testing flashcards as text
When conducting a hypothesis test, 'statistically significant' means:
Answer: The result is unlikely to occur by chance if H₀ is true.
Statistical significance only indicates the result is unlikely under H₀; it says nothing about practical importance.
A two-sided hypothesis test at α = 0.05 is equivalent to checking whether the 95% confidence interval:
Answer: Contains the null value.
If the null parameter value falls outside the 95% CI, we reject H₀ at α = 0.05 for a two-sided test.
Which scenario calls for a one-proportion z-test?
Answer: Testing whether the proportion of defective parts equals 0.05.
A one-proportion z-test is used when testing a single categorical proportion against a claimed value.
A test statistic falls in the rejection region. What does this mean?
Answer: The p-value is less than or equal to α.
When the test statistic falls in the rejection region, the p-value ≤ α and we reject H₀.
The significance level α represents:
Answer: The maximum acceptable probability of a Type I error.
Alpha (α) is set by the researcher as the tolerable risk of incorrectly rejecting a true H₀ (Type I error).
A study tests H₀: μ = 50 vs. Hₐ: μ > 50. The p-value is 0.12. At α = 0.05, the conclusion is:
Answer: Fail to reject H₀; insufficient evidence the mean exceeds 50.
Since 0.12 > 0.05, we fail to reject H₀ — there is not enough evidence to support the claim that μ > 50.
Which of the following increases the risk of a Type I error?
Answer: Raising the significance level from 0.01 to 0.05.
A higher α directly increases the probability of a Type I error because the rejection region widens.