1. Advanced Nursing t-Test and ANova SPSS EXPERT
Week 5 ANOVA Exercises Research Question: Is there a difference in the overall satisfaction
of women based on the number of housing problems (no problems, 1 problem, 2 or more
problems)? Using Polit2SetA dataset, run an ANOVA using Overall Satisfaction, Material
Well-Being (satovrl) as the dependent variable and Housing Problems (hprobgrp) (this is
the last variable in the dataset) as the Independent Variable. Follow these steps when using
SPSS: 1. Open Polit2SetA dataset. 2. Click Analyze then click Compare Means, then One-way
ANOVA. 3. Move the Dependent Variable (Overall Satisfaction “satovrl”) in the box labelled
Dependent List by clicking the arrow button. The dependent variable is a continuous
variable. 4. Move the Independent Variable (Housing Problems “Hprobgrp”) into the box
labelled Factor. The hprobgrp is a categorical variable coded as (1= no hoursing problem,
2=one housing problem, 3=two or more housing problems). 5. Click the Options button
(right side of box) and click on Descriptives and Homogeneity of Variance and then click
continue. 6. Click on Post Hoc (right side of box). Click on Tukey and then click continue. 7.
Click OK. 8. Check your answers against SPSS output provided. 9. Do not submit the SPSS
tables/output as answers to the questions. Assignment: Through analysis of the data and
use of the questions below, answer the questions on your findings from this ANOVA test.
Answers should be short and do not need to be written as a sentence. No ciattion or APA is
required. 1. 2. 3. 4. What is the total sample size? How many women were in each of the
different hprobgrp groups? What are the mean and standrad deviation (SD) overall
satisfaction scores for each group? Interpret the Levene’s statistic. (Hint: Is the assumption
of homogeneity of variance met? Are equal variances assumed or not assumed?) 5. What is
the value of the F-statistic, number of degrees of freedom and the p-value? 6. Is there a
significant difference in the overall satisfaction level of women in each of the hprobgrp
groups? 7. Interpret hoc test. When interpreting hoc test indicate the mean and standard
deviation for each group and indicate which group was signifantly higher or lower from the
other. If there is no difference between two groups indicate that as well. Week 5 t Test
Exercises SPSS Output Independent t test Group Statistics Currently employed? CES-D Score
N Mean Std. Deviation Std. Error Mean No 524 20.8965 12.46425 .54450 Yes 436 15.8239
10.13655 .48545 dimension1 Independent Samples Test Levene’s Test for Equality of
Variances t-test for Equality of Means 95% Confidence Interval of the Sig. (2- CES-D Equal
variances Score assumed Equal variances not assumed F Sig. t 23.615 .000 6.825 df tailed)
Mean Std. Error Difference Difference Difference Lower Upper 958 .000 5.07264 .74326
3.61404 6.53124 6.954 957.514 .000 5.07264 .72949 3.64107 6.50421 Dependent t test
2. Paired Samples Statistics Mean Pair 1 N Std. Deviation Std. Error Mean CES-D Score 18.5516
157 11.87462 .94770 CESD Score, Wave 1 17.8344 157 11.49908 .91773 Paired Samples
Correlations N Pair 1 CES-D Score & CESD Correlation 157 Sig. .412 .000 Score, Wave 1
Paired Samples Test Paired Differences 95% Confidence Interval of Mean Pair 1 CES-D
Score – CESD Score, Wave 1 .71718 Std. Std. Error Deviation Mean 12.67921 1.01191 the
Difference Lower -1.28164 Upper 2.71599 Sig. (2t .709 df 156 tailed) .480 Independent t
test with 3 outcome variables Group Statistics Educational attainment CES-D Score N Mean
Std. Deviation Std. Error Mean No high school diploma 453 20.1408 11.49986 .54031
Diploma or GED 475 17.5931 11.72389 .53793 SF12: Physical Health No high school
diploma 421 44.03546 10.781420 .525454 Component Score, Diploma or GED 440
46.27713 10.597265 .505205 SF12: Mental Health No high school diploma 421 45.70217
10.693544 .521171 Component Score, Diploma or GED 440 47.48328 10.895127 .519405
standardized standardized Independent Samples Test Levene’s Test for Equality of
Variances t-test for Equality of Means 95% Confidence Interval of the F CES-D Score Equal
variances .228 Sig. .633 t df Sig. (2- Mean Std. Error tailed) Difference Difference Difference
Lower Upper 3.340 926 .001 2.54776 .76278 1.05078 4.04474 3.342 925.265 .001 2.54776
.76243 1.05146 4.04406 -3.076 859 .002 -2.241671 .728649 -3.671812 -.811529 -3.075
855.772 .002 -2.241671 .728927 -3.672364 -.810977 -2.420 859 .016 -1.781113 .736103 -
3.225884 -.336341 -2.421 858.441 .016 -1.781113 .735800 -3.225290 -.336936 assumed
Equal variances not assumed SF12: Physical Equal variances Health assumed Component
Equal variances Score, not assumed 1.106 .293 standardized SF12: Mental Equal variances
Health assumed Component Equal variances Score, not assumed standardized .174 .677
Week 5 Independent t Test Exercises Answer the questions below for Part I II and III. Make
sure to create the table if asked and do not submit SPSS output as your answer. If you have
any questions, please email your instructor. Don’t forget to save the document as instructed
in the assignment submission directs. You do not have to submit a title page or reference list
for this assignment. No citations are required for your submission. Part I The hypothesis
being tested is: Women who are working will have a lower level of depression as compared
to women who are not working. Using Polit2SetC SPSS dataset, which contains a number of
mental health variables, determine if the above hypothesis is true. Follow these steps when
using SPSS: 1. 2. 3. 4. Open Polit2SetC dataset. Click Analyze then click Compare Means, then
Independent Sample T-test. Move the Dependent Variable (CES_D Score “cesd”) in the area
labelled Test Variable. Move the Independent Variable (Currently Employed “worknow”)
into the area labelled Grouping Variable. The worknow variable is coded as (0= those
women who do not work and 1= those women who are working). Click on Define Groups in
group 1 box type 0 and in group 2 box type 1. Click Continue. 5. Click continue and then click
OK. 6. Check your answers to the Week 5 t Test Excercises SPSS Output. Assignment:
Through analysis of the data answer the questions below with your findings from this t-test.
1. 2. 3. 4. How many women were employed versus not employed in the sample? What is
the total sample size? What are the mean and standard deviation for the CES-D scores for
each group? Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of
variance met? Are equal variances assumed or not assumed?) Why? 5. What is the value of
the t-statistic, number of degrees of freedom and the p-value? 6. Does the data support the
3. hypothesis? Why or why not? Part II Hypothesis: Women who reported depression scores
in wave 1 and wave 2 of the study did not have a significant difference in their level of
depression. Using Polit2SetC SPSS dataset, determine if the above hypothesis is true. Follow
these steps when using SPSS: 1. Open Polit2SetC dataset. 2. Click Analyze then click
Compare Means, then Paired Samples T-test. 3. First click on CES-D Score (cesd) and move it
into the box labelled Paired Variables (in the rectangle for Pair 1 of Variable 1 and then click
on CESD Score, Wave 1 (cesdwav1) and move it into the Paired Variables box (in the
rectangle next to CES-D Score, pair 1, variable 2). 4. Click continue and then click OK. 5.
Check your answers to the Week 5 t Test Excercises SPSS Output Assignment: Through
analysis of the data and answer the questions below for the findings from this ttest. 1. 2. 3.
4. 5. What is the total sample size? What are the mean and the standard deviation of the
CES-D scores at wave 1 and wave 2? What is the mean difference between the two time
periods? What is the value of the t-statistic, number of degrees of freedom and the p-
value(sig)? Does the data support the hypothesis? Why or why not? Part III Using Polit2SetC
dataset, run independent groups t-tests for three outcomes. The outcome variables are CES-
D Score (cesd), SF12: Physical Health Component Score, standardized (sf12phys) and SF12:
Mental Health Component Score, standardized (sf12ment). Follow these steps when using
SPSS: 1. Open Polit2SetC dataset. 2. Click Analyze then click Compare Means, then
Independent Sample T-test. 3. Move the Dependent Variables (CES_D Score “cesd”, SF12:
Physical Health Component Score, standardized (sf12phys), and SF12: Mental Health
Component Score, standardized (sf12ment) ) in the area labelled Test Variable. 4. Move the
Independent Variable (Educational Attainment “educatn”) into the area labelled Grouping
Variable. The educatn variable is coded as (1= no high school credential and 2=diploma or
GED). Click on Define Groups in group 1 box type 1 and in group 2 box type 2. Click
Continue. 5. Click continue and then click OK. 6. Check your answers to the Week 5 t Test
Excercises SPSS Output Assignment: Create a table to present your results, use the table 6.3
in Chapter 6 in your book as a model. Write one or two paragraphs explaining and
summarizing your results. Do not submit the SPSS output that is provided. Week 5 ANOVA
Exercises SPSS Output Descriptives Overall satisfaction, material well-being 95%
Confidence Interval for Mean N Mean Std. Deviation Std. Error Lower Bound Upper Bound
Minimum Maximum No Housing Problem 367 12.71 2.353 .123 12.47 12.95 4 16 One
Housing Problem 264 11.97 2.588 .159 11.66 12.28 4 16 Two or More Housing 304 10.57
2.594 .149 10.28 10.86 4 16 935 11.80 2.658 .087 11.63 11.97 4 16 Problems Total Test of
Homogeneity of Variances Overall satisfaction, material well-being Levene Statistic df1
2.109 df2 2 Sig. 932 .122 ANOVA Overall satisfaction, material well-being Sum of Squares
Between Groups df Mean Square 771.072 2 385.536 Within Groups 5826.111 932 6.251
Total 6597.183 934 F Sig. 61.674 .000 Multiple Comparisons Overall satisfaction, material
well-being Tukey HSD (I) Housing Problems (J) Housing Problems 95% Confidence Interval
Mean Difference (I-J) No Housing Problem One Housing Problem Two or More Housing Std.
Error Sig. Lower Bound Upper Bound .739* .202 .001 .27 1.21 * 2.139 .194 .000 1.68 2.59 -
.739* .202 .001 -1.21 -.27 * 1.401 .210 .000 .91 1.89 -2.139* .194 .000 -2.59 -1.68 * .210 .000
-1.89 -.91 Problems One Housing Problem No Housing Problem Two or More Housing
Problems Two or More Housing Problems No Housing Problem One Housing Problem *. The
4. mean difference is significant at the 0.05 level. -1.401 Week 5 ANOVA Exercises Research
Question: Is there a difference in the overall satisfaction of women based on the number of
housing problems (no problems, 1 problem, 2 or more problems)? Using Polit2SetA dataset,
run an ANOVA using Overall Satisfaction, Material Well-Being (satovrl) as the dependent
variable and Housing Problems (hprobgrp) (this is the last variable in the dataset) as the
Independent Variable. Follow these steps when using SPSS: 1. Open Polit2SetA dataset. 2.
Click Analyze then click Compare Means, then One-way ANOVA. 3. Move the Dependent
Variable (Overall Satisfaction “satovrl”) in the box labelled Dependent List by clicking the
arrow button. The dependent variable is a continuous variable. 4. Move the Independent
Variable (Housing Problems “Hprobgrp”) into the box labelled Factor. The hprobgrp is a
categorical variable coded as (1= no hoursing problem, 2=one housing problem, 3=two or
more housing problems). 5. Click the Options button (right side of box) and click on
Descriptives and Homogeneity of Variance and then click continue. 6. Click on Post Hoc
(right side of box). Click on Tukey and then click continue. 7. Click OK. 8. Check your
answers against SPSS output provided. 9. Do not submit the SPSS tables/output as answers
to the questions. Assignment: Through analysis of the data and use of the questions below,
answer the questions on your findings from this ANOVA test. Answers should be short and
do not need to be written as a sentence. No ciattion or APA is required. 1. What is the total
sample size? 2. How many women were in each of the different hprobgrp groups? 3. What
are the mean and standrad deviation (SD) overall satisfaction scores for each group? 4.
Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of variance met?
Are equal variances assumed or not assumed?) 5. What is the value of the F-statistic,
number of degrees of freedom and the p-value? 6. Is there a significant difference in the
overall satisfaction level of women in each of the hprobgrp groups? 7. Interpret hoc test.
When interpreting hoc test indicate the mean and standard deviation for each group and
indicate which group was signifantly higher or lower from the other. If there is no difference
between two groups indicate that as well. Answer 1: What is the total sample size? We are
considering a data of 935 individuals and take a sample of size is 935. Answer 2: How many
women were in each of the different hprobgrp groups? From 935 sample size, 367, 264 and
304 respectively fall in the groups of no Housing Problem, One Housing Problem and Two
or More Housing Problems. Answer 3: What are the mean (SD) overall satisfaction scores
for each group? The above result shows that the mean (sd), by the overall satisfaction
scores are mean 12.71 sd 2.353, mean 11.97 sd 2.588 and mean 10.57 sd 2.594 respectively
for the groups No Housing Problem, One Housing Problem and Two or More Housing
Problems. The overall mean satisfaction scores is 11.80 while sd satisfaction scores is 2.658.
Answer 4: Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of
variance met? Are equal variances assumed or not assumed?) We use Levene’s test is used
to test whether the variances of the groups are same or significantly different. The null
hypothesis is that the variances are not significantly different. The obtained output
indicated that the test statistic is 2.109 with associated p-value of 0.122. As the p-value is
larger than the significance level of 0.05. Hence the null hypothesis was not rejected as the
variances are not significantly different across the groups thus the assumption of
homogeneity of variance are met. Answer 5: What is the value of the F-statistic, number of
5. degrees of freedom and the p-value? The result shows that the test statistic is 61.974 with
associated p-value 0.000. Answer 6: Is there a significant difference in the overall
satisfaction level of women in each of the hprobgrp groups? As the p-value is lower
compared to the significance level 0.05, thus null hypothesis may not be rejected. Therefore,
the result above result to the assumption that, the variances are not significantly distinct
across the groups. In addition, the homogeneity assumption of variance is met. By the
ANOVA test, we see that F-statistic value is 61.674 with df of between groups, 2 and that of
within groups 932 .Similarly, the related p-value is 0.000. We clearly see that the Ftest p-
value is lower compared to the significance level of 0.05 thereby we reject the null
hypothesis. In addition, we finalize that there is a major difference in the whole satisfaction
level of women in every of the hprobgrp groups. Answer 7: Interpret hoc test. When
interpreting hoc test indicate the mean and standard deviation for each group and indicate
which group was signifantly higher or lower from the other. If there is no difference
between two groups indicate that as well. hoc analysis is utilized for the analysis. As there
is major group’s differences, we have to recognize the specific group that varies. The output
display that p-values of hoc test for every pair is much smaller compared to the significance
level of 0.05. Therefore, every group means are significantly distinct. Therefore, every group
has significantly dissimilar mean. The descriptive statistics shows that the group of No
Housing Problem has the higher mean. In addition, the group with Two or More Housing
Problems has lower mean.
