1. If a researcher takes a large enough sample, he/she will almost always obtain:
a. virtually significant results
b. practically significant results
c. consequentially significant results
d. statistically significant results
2. The null and alternative hypotheses divide all possibilities into:
a. two sets that overlap
b. two non-overlapping sets
c. two sets that may or may not overlap
d. as many sets as necessary to cover all possibilities
3. Which of the following is true of the null and alternative hypotheses?
a. Exactly one hypothesis must be true
b. both hypotheses must be true
c. It is possible for both hypotheses to be true
d. It is possible for neither hypothesis to be true
4. One-tailed alternatives are phrased in terms of:
b. < or >
c. » or =
5. The chi-square goodness-of-fit test can be used to test for:
a. significance of sample statistics
b. difference between population means
6. A type II error occurs when:
a. the null hypothesis is incorrectly accepted when it is false
b. the null hypothesis is incorrectly rejected when it is true
c. the sample mean differs from the population mean
d. the test is biased
7. Of type I and type II error, which is traditionally regarded as more serious?
a. Type I
b. Type II
c. They are equally serious
d. Neither is serious
8. You conduct a hypothesis test and you observe values for the sample mean and sample standard deviation when n = 25 that do not lead to the rejection of .png”>. You calculate a p-value of 0.0667. What will happen to the p-value if you observe the same sample mean and standard deviation for a sample > 25?
c. Stay the same
d. May either increase or decrease
9. The form of the alternative hypothesis can be:
c. neither one nor two-tailed
d. one or two-tailed
10. A two-tailed test is one where:
a. results in only one direction can lead to rejection of the null hypothesis
b. negative sample means lead to rejection of the null hypothesis
c. results in either of two directions can lead to rejection of the null hypothesis
d. no results lead to the rejection of the null hypothesis
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