Chapter 9 Quiz
If a hypothesis test leads to the rejection of the null hypothesis, a:
Type I error may have been committed.
The error of rejecting a true null hypothesis is:
a Type I error.
In hypothesis testing, the critical value is:
a number that establishes the boundary of the rejection region.
If a hypothesis is not rejected at a 5% level of significance, it will:
also not be rejected at the 1% level.
As a general guideline, the research hypothesis should be stated as the:
alternative hypothesis.
For a two-tailed test with a sample size of 40, the null hypothesis will not be rejected at a 5% level of significance if the test statistic is:
between -1.960 and 1.960, exclusively.
For a two-tailed hypothesis test about a population mean, the null hypothesis can be rejected if the confidence interval:
does not include μ0.
A two-tailed test is a:
hypothesis test in which rejection region is in both tails of the sampling distribution.
An example of statistical inference is:
hypothesis testing.
In tests about a population proportion, p0 represents the:
hypothesized population proportion.
If a hypothesis test has a Type I error probability of .05, that means:
if the null hypothesis is true, it will be rejected 5% of the time.
When the rejection region is in the lower tail of the sampling distribution, the p-value is the area under the curve:
less than or equal to the test statistic.
If the cost of a Type I error is high, a smaller value should be chosen for the:
level of significance.
The level of significance is the:
maximum allowable probability of Type I error.
Two approaches to drawing a conclusion in a hypothesis test are:
p-value and critical value.
When the p-value is used for hypothesis testing, the null hypothesis is rejected if:
p-value ≤ α
A p-value is the:
probability, when the null hypothesis is true, of obtaining a sample result that is at least as unlikely as what is observed.
The level of significance in hypothesis testing is the probability of:
rejecting a true null hypothesis.
A two-tailed test is performed at a 5% level of significance. The p-value is determined to be .09. The null hypothesis:
should not be rejected.
In hypothesis testing, the alternative hypothesis is:
the hypothesis concluded to be true if the null hypothesis is rejected.
In hypothesis testing, the hypothesis tentatively assumed to be true is:
the null hypothesis.
The probability of making a Type I error is denoted by:
α
In order to test the hypotheses H0: μ ≤ 100 and Ha: μ > 100 at an α level of significance, the null hypothesis will be rejected if the test statistic z is:
≥ zα