Quiz (Chapter 8)
Effect Size, Power, CIs, and Bonferroni
The SevenStep Version of Hypothesis Testing
 (T/F) The last step of the 7step version of hypothesis testing involves
determining whether Ho is true.
 (T/F) A result that's statistically significant can be completely
devoid of any practical significance.
 The "yardstick" that's used to measure practical significance is
called
 actual significance
 credibility
 effect size
 importance
 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?
 (T/F) Effect size can be measured numerically.
 What three words do researchers use to describe the 3 different
"sizes" of effect size?
 What exactly would it mean if a researcher stated that his/her statistical
test had a power of .90?
 In a post hoc power analysis, is the effect size computed
by the researcher or is it chosen by him/her?
 If Ho is not rejected but statistical power is quite high,
would the chances of a Type II error be high or low?
The NineStep Version of Hypothesis Testing
 How many steps of the 6step version of hypothesis testing appear
in the 9step version of hypothesis testing?
 (T/F) In the 9step version of hypothesis testing, the researcher
specifies ES after analyzing the sample data.
 (T/F) In the 9step version of hypothesis testing, the sample
data are analyzed before a power level is specified.
 Of the 2 kinds of effect size measures ("standardized" or "raw"),
which one is better?
 (T/F) The needed sample size for a study cannot be determined unless
both ES & power are specified first.
 In Excerpt 8.9, if the n had been 50, the power would have been
___ (higher/lower) than .8.
 In Excerpt 8.10, which kind of effect size was used, standardized
or raw?
 There is general agreement that power should be no lower than ___
.
 (T/F) If a researcher reaches a failtoreject decision at the end
of the 9step version of hypothesis testing, a critic cannot
legitimately argue that a Type II error was made because the test was
too insensitive.
Hypothesis Testing Using Confidence Intervals
 (T/F) When hypothesis testing is conducted via one or more
confidence intervals, there's no Ho or Ha.
 If a 95% confidence interval is used when doing hypothesis testing,
the level of significance = ___ .
 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)?
 (Yes/No) In Excerpt 8.14, is the number .80 indicating statistical
power?
 (T/F) 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.
Adjusting for an Inflated Type I Error Rate
 (T/F) A Type I error is made when a researcher failstoreject
a null hypothesis that's really false.
 If you blindly select 1 card from a single wellshuffled 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 wellshuffled decks of cards. Here,
the probability that you'll end up with at least one club in
your set of 3 cards is:
 .25
 less than .25
 more than .25
 Do the terms "heightened probability of Type I error" & "inflated
Type I error risk" mean the same thing?
 Would the Bonferroni adjustment technique ever be used in a study
involving a single null hypothesis?
 (T/F) In Excerpt 8.19, the plevel of .017 would have been .025 if
there had been 2 comparisons (rather than 3 comparisons).
 When the Bonferroni adjustment technique is used, critical values
become ____ (more/less) demanding.
 Researchers sometimes use the "_____ modification" rather than the
Bonferroni adjustment technique.
A Few Cautions
 (T/F) The notion of an "effect size" (in the 7step version of hypothesis
testing) is exactly the same as the notion of an "effect size" (in the
9step version of hypothesis testing).
 (T/F) 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.
 (T/F) The 6step version of hypothesis testing fails completely
to address the distinction between statistical significance and practical
significance.
 (Yes/No) 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.
Two Questions that are Supposed to be a Bit Challenging
 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 Bonferronicorrected alpha level should be used if the researcher
desires to have a 5% chance of one or more Type I errors occurring?
 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 2tailed 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?
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