This document contains 30 multiple choice and calculation questions related to statistical analysis. It asks about statistical procedures such as ANOVA, t-tests, correlation, and significance testing. It provides data sets and asks the reader to calculate statistics and determine if results are statistically significant. It also asks the reader to identify the appropriate statistical analyses for different research study designs.

1. 1. What would be the appropriate statistical procedure to test
the following hypothesis: “Triglyceride values are a good
predictor of weight in obese adults.”
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2. What is (are) the function(s) of parametric statistical
procedures?
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3. What is Type I Error?
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4. What are the assumptions underlying the use of parametric,
statistical procedures?
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2. ________________________________________________
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5. If a critical value is greater than the test statistic, would
you accept or reject the null hypothesis?
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6. Under what circumstance(s) is it appropriate to use a 2-
tailed test of significance?
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7. What is the appropriate statistical procedure to use when
your interest is in detecting a bivariate, curvilinear association?
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8. For a study comparing outcomes under alternate treatment
conditions, when the null hypothesis is rejected, the researcher
concludes that a difference among groups exists.
_____True
_____False
9. A researcher, for reasons passing understanding, wishes to
assess the association between gender and total cholesterol
values. What would be the appropriate statistical procedure?

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10. An HIV educator wishes to determine whether the method
of delivering teaching influences adherence with antiretroviral
therapy. She decides to measure adherence as viral load (a ratio
measure). She teaches one group using lecture-discussion
techniques. She adapts the information for access on the
internet and gives another group the information using this
medium. For yet another group, she decides to give a CD Rom
for home study and then meets with individuals to answer any
questions. She obtains viral loads for all clients for
comparison. What procedure will determine the significance of
any differences?
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Items 11-15 relate to the following study results:
Study AStudy BStudy C
2 = 1.683 F = 7.357 r = .83
df = 4 df = 3/203 df = 98
p > .05 p < .05 p < .01
11. What statistical procedure was used to analyze data in
study B?
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12. How many groups were compared in study B?
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13. How many subjects were enrolled in Study C?
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14. Which study demonstrated the greatest level of statistical
significance?
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15. In which study is the likelihood of Type I error greatest?
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Items 16, 17 and 18 relate to the following:
In a regression analysis, a nurse researcher found a correlation
of .82 between pain relief scores and satisfaction with nursing
care. She also calculated the following for her regression
analysis:
Pain Relief (x): Mean = 58 sd = 3.9
Satisfaction (y): Mean = 42 sd = 4.4
slope = 1.56
y intercept = - 3.53
16. What will be the predicted satisfaction score (expressed as
a point estimate) for a patient with a pain relief score of 62?

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17. What is the standard error of estimate when predicting
satisfaction from knowledge of pain relief score?
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18. What would be the interval estimate for satisfaction for the
patient in problem 16?
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Items 19-21: A nurse researcher is investigating the effect of
timing of standard pain control interventions on severity of pain
in adolescents with sickle-cell disease. She establishes three
treatment protocols: 1) initiation of pain control immediately
upon the presence of prodromal sign (an “aura” signaling the
imminent onset of pain); 2) initiation of pain control one hour
after the onset of pain; and 3) initiation of pain control only at
the points where non-steroidal anti-inflammatories and guided

6. imagery are no longer effective in keeping pain bearable. She
conducted a one-way ANOVA to analyze her data and the
following table summarizes her findings:
Source df SS MSS F p
Among 2 75536.2 37768.1 5.159
<.05
Within 27 197660.3 7320.8
Total 29 273196.5
On the basis of these data alone, she drew the following
conclusions. For each conclusion, indicate whether you feel the
conclusion is justified or unjustified.
19. Severity of pain is influenced by the timing of pain
interventions in sickle-cell crises.
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20 Immediate intervention is better than either slightly
delayed intervention or initiation at crisis stage.
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21. She has more than 99% confidence in her conclusion that
severity of pain is influenced by timing.
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Items 22-23 relate to the following study results:
Study AStudy B
r = .64 r = .77
df = 18 df = 121

7. p<.05 p<.01
22. In using the data from study A to make predictions, what
percent of the time would you expect predictions to be exactly
correct?
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23. Which study would have the smallest margin of error in
predicting one variable from knowledge of the other?
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Items 24 and 25 relate to the following SPSS output. A
researcher is interested in characteristics of HIV+ and HIV-
adolescents interviewed 166 young adults about their
experiences during adolescence. He wished to know, among
other things, if there were significant differences in the ages at
which HIV+ and HIV- young adults became sexually active.
The following is the printout of this analysis:
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HIV Status N Mean sd Stnd.
Error
Age at Positive 57 13.2 2.96576 .39282
first sexual
experience Negative 109 15.1 2.57286 .24644
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Independent Samples Test
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Levene’s Test for
Equality of Variances

8. F Sig
Age at Equal variance assumed 1.313 .254
first sexual
experience Equal variance not assumed
t-test for Equality of Means
t df sig. mean difference
Age at Equal variance assumed -2.870 164 .005
-1.9
first sexual
experience Equal variance not assumed -2.745 99.66
.007 -1.9
24. Were there significant differences between the groups.
Give the relevant stastical data to support your answer?
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25. What is the confidence interval associated with your
answer to item # 24?
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9. Each of the questions on the following pages is a calculation
problem worth 10 points. Partial credit will be awarded if I can
following your procedures and determine that errors are
arithmetic rather than conceptual. It would be wise, therefore,
to clearly indicate your worksteps on each problem.
26. For the following data set, calculate the oneway ANOVA
and test for significance at the .05 level.
Group 1Group 2Group 3Group 4
xx2xx2xx2xx2
7 49 10 100 12 144 16 256
8 64 12 144 14 196 15 225
7 49 13 169 13 169 18 324
9 81 13 169 11 121 17 289
9 81 14 196 13 169 20 400
11 121 15 225 15 225 21 441
10100141961316922484
61 545 91 1,199 91 1,193
129 2,419

10. 27. Calculate the 2 for the following 3 X 2 table and test for
significance at the .01 level.
Group 1 Group 2 Group 3
Positive
Outcome 9 12 8 29
Negative
Outcome 5 16 4 25
14 28 12 54

11. 28. For the following group data, calculate a t-test and test for
significance at the .05 level, 2-tailed level of significance.
Treatment GroupControl Group
Mean = 68.4 Mean = 52.2
sd = 5.6 sd = 6.0
n = 42 n = 46

12. 29. For the following paired observations, calculate the
Pearson product-moment correlation coefficient and test for

13. significance at the .01 level.
xx2yy2xy
17 289 23 529 391
17 289 19 361 323
18 324 20 400 360
19 361 17 289 323
21 441 15 225 315
22 484 19 361 418
21 441 20 400 420
23 529 19 361 437
22 484 20 400 440
1832416256288
198 3,966 188 3,582
3,715

14. 30. For the following data regarding paired rank orders for a
sample, calculate the correlation coefficient and test for
significance at the .05 level.
Subject #Rank 1Rank 2
1 2 1
2 1 2.5
3 3 2.5
4 5 4
5 6 5
6 4 8
7 7 6
8 9 7
9 8 10
10 10 9