Chapter 6

Question 1

alpha or alpha level

Answer 1

the probability of making a Type I error; the probability that a result will fall in the rare zone and the null hypothesis will be rejected when the null hypothesis is true; often called significance level; abbreviated α; usually set at .05 or 5%.

Question 2

alternative hypothesis

Answer 2

abbreviated H1; a statement that the explanatory variable has an effect on the outcome variable in the population; usually, a statement of what the researcher believes to be true.

Question 3

beta

Answer 3

the probability of making a Type II error; abbreviated β.

Question 4

the common zone

Answer 4

the section of the sampling distribution of a test statistic in which the observed outcome should fall if the null hypothesis is true; typically, 95% of the sampling distribution.

Question 5

critical value

Answer 5

the value of the test statistic that forms the boundary between the rare zone and the common zone of sampling distribution of the test statistic.

Question 6

hypothesis

Answer 6

a proposed explanation for observed facts; a statement or prediction about a population value.

Question 7

hypothesis testing

Answer 7

a statistical procedure in which data from a sample are used to evaluate a hypothesis about a population.

Question 8

nonrobust assumption

Answer 8

an assumption for a statistical test that must be met in order to proceed with the test.

Question 9

null hypothesis

Answer 9

abbreviated H0; a statement that in the population the explanatory variable has no impact on the outcome variable.

Question 10

one-tailed hypothesis test

Answer 10

hypothesis that predicts the explanatory variable has an impact on the outcome variable in a specific direction.

Question 11

p value

Answer 11

the probability of Type I error; the same as alpha level or significance level.

Question 12

power

Answer 12

the probability of rejecting the null hypothesis when the null hypothesis should be rejected.

Question 13

rare zone

Answer 13

the section of the sampling distribution of a test statistic in which it is unlikely an observed outcome will fall if the null hypothesis is true; typically, 5% of the sampling distribution.

Question 14

robust assumption

Answer 14

an assumption for a statistical test that can be violated to some degree and it is still OK to proceed with the test.

Question 15

significance level

Answer 15

the probability of Type I error; the same as alpha level or p value.

Question 16

statistically significant

Answer 16

when a researcher concludes that the observed sample results are different from the null-hypothesized population value.

Question 17

two-tailed hypothesis test

Answer 17

hypothesis that predicts the explanatory variable has an impact on the outcome variable but doesn’t predict the direction of the impact.

Question 18

Type I error

Answer 18

the error that occurs when the null hypothesis is true but is rejected; p(Type I error) = α.
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Question 19

Type II error

Answer 19

the error that occurs when we fail to reject the null hypothesis but should have rejected it; p(Type II error) = β.