# Hypothesis Tests 3

9 Questions | Total Attempts: 1221  Settings  Evaluating and interpreting p-values

• 1.
Hypotheses in a significance test are always stated in terms of the population parameters.
• A.

True

• B.

False

• 2.
When a p-value is high, this means there is strong evidence against the null hypothesis
• A.

True

• B.

False

• 3.
If a p-value for a 2-sided test equals .065, the p-value for the 1-sided test using the same sample data will not be significant at the 1% level.
• A.

True

• B.

False

• 4.
A t-test is used when the population standard deviation for a mean is unknown.
• A.

True

• B.

False

• 5.
When a sample statistic is close to the believed population parameter, the p-value for a significance test will typically be low.
• A.

True

• B.

False

• 6.
If a 95% confidence interval for a population mean is (8.67, 11.26) then a 2-sided test for the hypothesis  will most likely find evidence to reject Ho at the 5% level.
• A.

True

• B.

False

• 7.
If the results of a hypothesis test are significant at the 1% level then they are also significant at the 5% level
• A.

True

• B.

False

• 8.
If the p-value is .013, the probability that Ho is true is only .013
• A.

True

• B.

False

• 9.
Review: The critical value (z*) used for a 99% confidence interval for a sample mean when the population standard deviation is known is 2.576
• A.

True

• B.

False

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