SPSS Homework 7 Instructions
Chi Square
Part 1:
Green & Salkind: Lesson 40, Exercises 1–4
The following helpful tips are numbered
... [Show More] to correspond with the exercise number to which they refer (a dash indicates that no tips are needed):
1. Use the method reviewed in the presentation to weight the cases for this data set. (no points—done in data file)
2. Do a, b, and c. (2 pts for output and 2 pts each for a–c)
3. ---------- (2 pts)
4. All homework “Results sections” must follow the example given in the Course Content document “Writing Results of Statistical Tests in Current APA Format” (Note: you do not have to refer to a figure). (2 pts)
Green & Salkind: Lesson 41, Exercises 1–3
The following helpful tips are numbered to correspond with the exercise number to which they refer (a dash indicates that no tips are needed):
Lilly collects data on a sample of 130 high school students to evaluate whether the proportion on female high school students who thake advanced mathe courses in high school varies demending upons whether they have been raised primiarily by their father or by both their mother and their father. The SPSS data File contains two variables: math (0 = no advanced math and 1 = some advanced math) and parent ( 1 = primararily father and 2 = father and mother)
NOTE: This exercise does not use the weighted cases method. Use the data file “as is.”
1. Do a, b, c, d, and e. For letter “e,” this question is asking specifically about effect size. (2 pts for output and 2 pts each for a–e)
Conduct a crosstabs analysis to examing whether the proportion of female high school students who take advanced mathe courses is different for different levels of the parent variable. From the output, identify the following:
Case Processing Summary
Cases
Valid
Missing
Total
N
Percent
N
Percent
N
Percent
Parents of female high school student * Math classes
130
100.0%
0
0.0%
130
100.0%
Parents of female high school student * Math classes Crosstabulation
Math classes
Total
No advanced math
Some advanced math
Parents of female high school student
Primarily father
Count
21
9
30
Expected Count
26.1
3.9
30.0
% within Parents of female high school student
70.0%
30.0%
100.0%
Father and mother
Count
92
8
100
Expected Count
86.9
13.1
100.0
% within Parents of female high school student
92.0%
8.0%
100.0%
Total
Count
113
17
130
Expected Count
113.0
17.0
130.0
% within Parents of female high school student
86.9%
13.1%
100.0%
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Exact Sig. (2-sided)
Exact Sig. (1-sided)
Pearson Chi-Square
9.826a
1
.002
Continuity Correctionb
7.986
1
.005
Likelihood Ratio
8.434
1
.004
Fisher's Exact Test
.004
.004
Linear-by-Linear Association
9.751
1
.002
N of Valid Cases
130
a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.92.
b. Computed only for a 2x2 table
Symmetric Measures
Value
Approx. Sig.
Nominal by Nominal
Phi
-.275
.002
Cramer's V
.275
.002
N of Valid Cases
130
a. Percentage of female students who took no advanced math classes? 13.1%
b. Percent of female students who took no advanced math classes when female students were raised by their fathers? 70.0%
c. Percent of female students raised by their father only?
d. χ2 value χ2 (1, N = 130) = 9.83
e. Strength of relationship between taking advanced math classes and level aof parenting
2. ---------- (2 pts) Create a clustered bar graph to show differences in the number of female students taking some advanced mathe classes for the different categories of parenting.
3. All homework “Results sections” must follow the example given in the Course Content document “Writing Results of Statistical Tests in Current APA Format” (Note: you do not have to refer to a figure). (2 pts)
Part 2:
1. An industrial/organizational (I/O) psychologist is helping a company determine the type of work stations preferred by its employees. The business owner believes that people who work in different departments may prefer different work station layouts. In order to examine this claim, the I/O psychologist sets up 3 simulated work stations: private office (PO), semi-private office (SPO), and open floor plan (OFP). She recruits employees from 3 different departments: Information Technology, Human Resources, and Marketing. The participants spend 30 minutes in each simulated work station performing general pre-arranged tasks. At the end of the 1.5 hours, the participants turn in a form on which they mark which work station they prefer. The results are listed in the table on the following page. Perform a chi square test of independence (using an SPSS two-way contingency table analysis) to determine whether the proportions of work station preferences differ across departments. Use the weighted cases method.
The steps will be the same as the ones you have been practicing in Part 1 of the assignment—the only difference is that you are now responsible for creating the data file as well. Remember to name and define your variables under the “Variable View,” then return to the “Data View” to enter the data. (2 pts)
Private Office
Semi-Private Office
Open Floor Plan
TOTAL
Information Technology
9
6
4
19
Human Resources
6
10
3
19
Marketing
7
3
9
19
TOTAL
22
19
16
57
2. Create a clustered bar graph depicting your results. (2 pts)
3. Write an APA-style Results section describing the outcome. All homework “Results sections” must follow the example given in the Course Content document “Writing Results of Statistical Tests in Current APA Format” (Note: you do not have to refer to a figure). (2 pts)
Part 3: Cumulative Homework
1. A researcher wants to find out if the number of absences from a chemistry class are predictive of final exam scores at a local university. The data from the past term are in the table below. Are number of absences predictive of final exam scores? Choose the correct test to analyze this question, set up the SPSS file, and run the analysis. Follow the directions on the following page.
Number of Absences
Final Exam Scores
1
1
2
3
4
5
5
5
6
6
6
7
7
98
95
89
89
80
85
80
75
76
69
70
62
60
a) Paste appropriate SPSS output. (2 pts)
b) Paste appropriate SPSS graph. (2 pts)
c) Write an APA-style Results section describing the outcome. All homework “Results sections” must follow the example given in the Course Content document “Writing Results of Statistical Tests in Current APA Format” (Note: you do not have to refer to a figure). (2 pts)
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week 7.
Part 4: Phase Study
It is time to present your findings. During this phase, you will write a short Results section in current APA style that presents the results of your statistical test as well as interprets these results in light of the research question. The Results section must be 1–2 paragraphs must include:
1. The results of your analysis, including the value of the appropriate test statistic, the significance level, and any other pertinent information (sample size, etc.).
2. Several sentences that interpret these results, including the following information:
· Were the results significant or not?
· Do these results lead you to accept or reject the null hypothesis?
· What are the strengths and weaknesses of the statistical test that was used?
· Are there any characteristics of the sample or the data collection method that should be taken into consideration when interpreting these results that you would mention briefly to the reader?
Remember that the Results section is not a Discussion section. Therefore, it is NOT the place to make any wide-ranging statements about doctrine in general, how surprised (or not surprised) you are by the results, whether they correspond with other research, etc. You will have a chance in the last phase of the lab to share your thoughts and insights, but remember for this phase that Results sections focus on data. Use the sections in your textbooks as guides concerning content and style. You can also use the Publication Manual of the American Psychological Association as a guide (if you have one), or visit this website for more guidance: http://web.psych.washington.edu/writingcenter/writingguides/pdf/stats.pdf
Descriptive Statistics
Mean
Std. Deviation
N
per_god
4.2857
1.06904
14
jc_god
4.1429
1.16732
14
jc_rose
4.1429
1.16732
14
plp_good
3.0714
.82874
14
jc_sacrifice
4.1429
1.09945
14
gdev_cir
2.6429
1.00821
14
gdwrd_true
4.5714
.51355
14
fthjc_hvn
4.4286
.75593
14
gfgs_ghs
4.5000
.75955
14
total_und
35.9286
35.08334
14
Correlations
per_god
jc_god
jc_rose
plp_good
jc_sacrifice
gdev_cir
gdwrd_true
fthjc_hvn
gfgs_ghs
total_und
per_god
Pearson Correlation
1
.951**
.951**
-.025
.944**
-.326
.240
.027
.189
.216
Sig. (2-tailed)
.000
.000
.933
.000
.255
.408
.926
.517
.458
N
14
14
14
14
14
14
14
14
14
14
jc_god
Pearson Correlation
.951**
1
1.000**
.068
.942**
-.215
.367
.274
.434
.276
Sig. (2-tailed)
.000
.000
.817
.000
.461
.197
.343
.121
.339
N
14
14
14
14
14
14
14
14
14
14
jc_rose
Pearson Correlation
.951**
1.000**
1
.068
.942**
-.215
.367
.274
.434
.276
Sig. (2-tailed)
.000
.000
.817
.000
.461
.197
.343
.121
.339
N
14
14
14
14
14
14
14
14
14
14
plp_good
Pearson Correlation
-.025
.068
.068
1
.072
.033
-.103
.070
.061
.117
Sig. (2-tailed)
.933
.817
.817
.806
.911
.725
.812
.836
.691
N
14
14
14
14
14
14
14
14
14
14
jc_sacrifice
Pearson Correlation
.944**
.942**
.942**
.072
1
-.367
.253
.198
.276
.341
Sig. (2-tailed)
.000
.000
.000
.806
.197
.383
.497
.339
.232
N
14
14
14
14
14
14
14
14
14
14
gdev_cir
Pearson Correlation
-.326
-.215
-.215
.033
-.367
1
.127
.115
.251
.021
Sig. (2-tailed)
.255
.461
.461
.911
.197
.664
.695
.386
.943
N
14
14
14
14
14
14
14
14
14
14
gdwrd_true
Pearson Correlation
.240
.367
.367
-.103
.253
.127
1
.510
.789**
-.164
Sig. (2-tailed)
.408
.197
.197
.725
.383
.664
.063
.001
.575
N
14
14
14
14
14
14
14
14
14
14
fthjc_hvn
Pearson Correlation
.027
.274
.274
.070
.198
.115
.510
1
.804**
.317
Sig. (2-tailed)
.926
.343
.343
.812
.497
.695
.063
.001
.269
N
14
14
14
14
14
14
14
14
14
14
gfgs_ghs
Pearson Correlation
.189
.434
.434
.061
.276
.251
.789**
.804**
1
.206
Sig. (2-tailed)
.517
.121
.121
.836
.339
.386
.001
.001
.479
N
14
14
14
14
14
14
14
14
14
14
total_und
Pearson Correlation
.216
.276
.276
.117
.341
.021
-.164
.317
.206
1
Sig. (2-tailed)
.458
.339
.339
.691
.232
.943
.575
.269
.479
N
14
14
14
14
14
14
14
14
14
14
**. Correlation is significant at the 0.01 level (2-tailed). [Show Less]