Quiz (Chapter 8)


Effect Size, Power, CIs, and Bonferroni

The Seven-Step Version of Hypothesis Testing
  1. The last step of the 7-step version of hypothesis testing involves determining whether Ho is true.
    2. True
    False
  2. A result that's statistically significant can be completely devoid of any practical significance.
    3. True
    False
  3. The "yardstick" that's used to measure practical significance is called
    4. actual significance
    credibility
    effect size
    importance
  4. Look at Excerpts 8.3, 8.4, 8.5, and 8.6. In these excerpts, what 4 letters were used to represent measures of effect size?
    5. e, n, u, and W
    r, d, f, and V
  5. Effect size can be measured numerically.
    6. True
    False
  6. What three words do researchers use to describe the 3 different "sizes" of effect size?
    7. small, medium, large
    tiny, so-so, gigantic
    trivial, moderate, impressive
    worthless, typical, outstanding
  7. If a researcher stated that his/her statistical test had a power of .90, this would mean that there is a 90% of what occurring?
    8. Reaching a "reject" decision when the null hypothesis is true.
    Reaching a "fail-to-reject" decision when the null hypothesis is true.
    Reaching a "reject" decision when the null hypothesis is false.
    Reaching a "fail-to-reject" decision when the null hypothesis is false.
  8. In a post hoc power analysis, is the effect size is computed by the researcher or is it chosen by him/her?
    9. Computed
    Chosen
  9. If Ho is not rejected but statistical power is quite high, would the chances of a Type II error be high or low?
    10. High
    Low
The Nine-Step Version of Hypothesis Testing
  1. How many steps of the 6-step version of hypothesis testing appear in the 9-step version of hypothesis testing?
    2. 3 of them
    4 of them
    5 of them
    All 6
  2. In the 9-step version of hypothesis testing, the researcher specifies ES after analyzing the sample data.
    3. True
    False
  3. In the 9-step version of hypothesis testing, the sample data are analyzed before a power level is specified.
    4. True
    False
  4. Of the 2 kinds of effect size measures ("standardized" or "raw"), which one is better?
    5. Standardized
    Raw
    Either is as good as the other
  5. The needed sample size for a study cannot be determined unless both ES & power are specified first.
    6. True
    False
  6. In Excerpt 8.9, if the n had been 50, the power would have been ___ (higher/lower) than .8.
    7. lower
    higher
  7. In Excerpt 8.10, which kind of effect size was used, standardized or raw?
    8. Standardized
    Raw
  8. There is general agreement that power should be no lower than ___ .
    9. .05
    .50
    .80
    .90
    .95
  9. If a researcher reaches a fail-to-reject decision at the end of the 9-step version of hypothesis testing, a critic cannot legitimately argue that a Type II error was made because the test was too insensitive.
    10. True
    False
Hypothesis Testing Using Confidence Intervals
  1. When hypothesis testing is conducted via one or more confidence intervals, there's no Ho or Ha.
    2. True
    False
  2. If a 95% confidence interval is used when doing hypothesis testing, what is the level of significance?
    3. .05
    .95
    Any value the researcher wants, but it must be lower than .95.
    Any value the researcher wants, but it must be higher than .95.
  3. If a researcher has a sample with data on two variables, if r = +.40, and if a 95% confidence interval around r extends from +.20 to +.57, should Ho be rejected if Ho: r = 0 (and Ha: r  0)?
    4. Yes
    No
  4. In Excerpt 8.14, is the number .80 indicating statistical power?
    5. Yes
    No
  5. If, in Excerpt 8.15, 40% of the people in the supervised group had improved, the result might have been a nonsignificant difference between the two groups.
    6. True
    False
Adjusting for an Inflated Type I Error Rate
  1. A Type I error is made when a researcher fails-to-reject a null hypothesis that's really false.
    2. True
    False
  2. If you blindly select 1 card from a single well-shuffled deck of cards, the probability that your card will be a "club" is .25 (i.e., 1 out of 4).  Instead of doing that, suppose you blindly select a single card from each of 3 well-shuffled decks of cards.  Here, the probability that you'll end up with at least one club in your set of 3 cards is:
    3. .25
    less than .25
    more than .25
  3. Do the terms "heightened probability of Type I error" & "inflated Type I error risk" mean the same thing?
    4. Yes
    No
  4. Would the Bonferroni adjustment technique ever be used in a study involving a single null hypothesis?
    5. Yes
    No
  5. In Excerpt 8.19, the p-level of .017 would have been ___ if there had been 2 comparisons (rather than 3 comparisons).
    6. .17
    .05
    .02
    .025
  6. When the Bonferroni adjustment technique is used, critical values become ____ demanding.
    7. more
    less
  7. Researchers sometimes use the "_____ modification" rather than the Bonferroni adjustment technique.
    8. Cohen-Dunn
    Cohen-Sidak
    Dunn-Sidak
A Few Cautions
  1. The notion of an "effect size" (in the 7-step version of hypothesis testing) is exactly the same as the notion of an "effect size" (in the 9-step version of hypothesis testing).
    2. True
    False
  2. The numerical criteria for "small," "medium," and "large" effects remain the same regardless of the statistical focus or the kind of ES that's computed.
    3. True
    False
  3. The 6-step version of hypothesis testing fails completely to address the distinction between statistical significance and practical significance.
    4. True
    False
  4. If 21 null hypotheses are tested, each at a=.05, and if Ho is true in each and every one of the 21 cases, would it be smart to bet that one or more Type I errors will be made among the 21 tests.
    5. Yes
    No
Two Questions that are Supposed to be a Bit Challenging
  1. If all bivariate correlations are computed among 5 variables, and if each r is tested to see of it is significantly different from 0, what Bonferroni-corrected alpha level should be used if the researcher desires to have a 5% chance of one or more Type I errors occurring?
    2. .05
    .01
    .005
  2. Suppose 2 researchers (Mary & Larry) each secretly pull a sample from the same giant population.  They both measure their subjects on the same 2 variables (X & Y), they both test Ho: r = 0, they both conduct a 2-tailed test, and they both set a= .05.  If Mary uses 5,000 subjects while Larry uses only 50, will Mary's Type I Error rate be "inflated" as compared to Larry's?
    3. Yes
    No

 

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