  Quiz Over 2nd Half of Chapter 7 (pp. 144-159) of the 6th Edition

Hypothesis Testing

A different quiz covered the 1st half of Ch. 7 (Steps 1, 2 , 4, & 6)

Step #5:  The Criterion for Evaluating the Sample Evidence
1. In testing Ho: m1=m2, what decision would be made (in Step #6) if the 2 sample means are the same.
2.  Reject Fail-to-reject
3. In a correlational study, if we somehow knew that r = 0.00, should we expect a random sample to yield data such that r = 0.00?
4.  Yes No
5. "If the difference between the data and __ (Ho/Ha) is judged to be ___ (small/large), then the sample data are looked upon as being inconsistent with Ho and, as a consequence, Ho will be ___ (rejected/retained)."
6.  Ho; small; rejected Ho; small; retained Ho; large; rejected Ho; large; retained Ha; small; rejected Ha; small; retained Ha; large; rejected Ha; large; retained
7. In Step #5, the calculated value can be compared against a criterion number that comes from a statistical table.  That criterion number is called the _____ .
8.  Critical value Demarcation line Test statistic Threshold value
9. If the calculated value exceeds the criterion number obtained from a statistical table, will Ho be rejected?
10.  Yes No Maybe
11. Normally, the critical value is not presented in the journal article.
12.  True False
13. If a researcher compares the data-based p-value with the level of significance (instead of comparing the calculated value with a critical value), Ho will be rejected if p is _______ than the level of significance.
14.  smaller larger
15. A small p-value indicates that the sample data deviate _____ from what would be expected if the null hypothesis was true.
16.  a little a lot
17. Which procedure gives the researcher the better chance to reject Ho, comparing the data-based p-value vs. the significance level OR comparing the calculated value vs. the critical value?
18.  Comparing the p-value with the significance level Comparing the calculated value with the critical value Neither procedure gives the researcher a better chance of rejecting
Step #3:  Selecting the Level of Significance
1. The level of significance is like a scientific cut-off point that allows the researcher to determine whether the discrepancy between the sample evidence and Ho should be labeled "small" or "large."
2.  True False
3. Should a researcher determine the level of significance before or after the sample data are collected?
4.  Before After
5. What level of significance is used most frequently by applied researchers?
6.  .001 .01 .05 .10 .25
7. What is the name of the lower-case Greek letter that denotes the significance level, and what does that letter look like?
8.  alpha; s alpha; b alpha; a sigma; s sigma; b sigma; a
9. The hypothesis testing procedure does not allow one to prove that the null hypothesis is true, but it does permit one to prove that the null hypothesis is false.
10.  True False
11. What type of mistake is made if a true null hypothesis is rejected? If a false null hypothesis is not rejected?
12.  Type I; Type II Type II; Type I
13. The chances of making a Type __ error are equal to the significance level.
14.  I II
15. If the level of significance is made more rigorous, this change will decrease the chances of a Type __ error but at the same time increase the chance of a Type __ error.
16.  Type I; Type II Type II; Type I
17. Which kind of error--Type I or Type II--is generally thought to be worse by the scientific community?
18.  Type I Type II
19. Do researchers ever choose a level of significance that's more "lenient" than the popular .05 level?
20.  Yes No
21. In Excerpt 7.23, the statement "p < 0.05" means the same thing as
22.  a < .05 a = .05 a > .05
23. The chance of a Type II error (like the chance of a Type I error) is determined solely by the alpha.
24.  True False
25. After making a decision about Ho, will the researcher be able to tell whether his/her decision was correct?
26.  Yes No
27. If a researcher rejects his/her Ho, does the level of significance indicate the probability that Hois true?
28.  Yes No
Results That Are Highly Significant and Near Misses
1. The level of significance influences the size of the tabled critical value.
2.  True False
3. A researcher might use the phrase "highly significant" if
4.  p > .999 p < .001
5. Whenever you see the notation "p < .01," you should presume that the researcher set alpha equal to .01.
6.  True False
7. A researcher might say that his/her results "approached significance" if the data-based p-level ends up being just slightly ______ than the level of significance.
8.  lower higher
9. Suppose a researcher sets alpha equal to .05 and then discovers, after analyzing the data, that p = .051. In summarizing his/her finding, what might this researcher might say?
10.  "There was a trend toward significance." "The result was not significant." He/she might say either of the things contained in the first two options.
A Few Cautions
1. Alpha should be a number close to 0 if it's referring to _____ but close to 1.0 if it's referring to _____.
2.  reliability; the level of significance validity; the level of significance the level of significance; reliability the level of significance; validity
3. Regarding Ho & Ha, which is/are normally specified in a journal article?
4.  Ho Ha Both Neither
5. If a researcher says that "the data support the hypothesis," to which hypothesis is he/she probably referring?
6.  Ho Ha Hr It could be either Ho or Ha It could be any of the 3: Ho, Ha, or Hr
7. If Ho is rejected at a very rigorous a-level, is it OK to conclude that something important has been revealed?
8.  Yes No
9. If a finding is "statistically significant," this means that it's big, important, and useful.
10.  True False