Topic: Chapter 9: Hypothesis Testing: Single Sample

Q1: The level of significance indicates the probability of rejecting a true null hypothesis.

True or False

Q2: You can make a Type I error when the null hypothesis is correct.

True or False

Q3. The power of a statistical test is the probability of rejecting a false null hypothesis.

True or False

Q4. In a hypothesis test about Mean, increasing the level of significance from 0.05 to 0.10 will raise the chance of a Type II error; other relevant factors being held constant.

True or False

Q5. In a hypothesis test about Mean, switching the significance level from .05 to .10 will make type I error more likely; other relevant factors being held constant.

True or False

Q6. The larger is the gap between the hypothesized mean and the actual Mean, the stronger is "the power of the test."

True or False

Q7. You cannot make a Type II error when the null hypothesis is correct.

True or False

Q8. A tire manufacturer has to find the average tensile strength of rubber in a particular tire brand. Assuming normality and a known population standard deviation, the manager uses a Z test to check that the mean tensile strength is 850 pounds per square inch. The calculated Z-value is a positive value that yields a p-value of 0.015. If the specified alpha is 0.01 is used, we reject the Null hypothesis.

True or False