Homework 7 Instructions Chi Square Part 1: Green & Salkind: Lesson 40, Exercises 1–4

SPSS Homework 7 InstructionsChi
SquarePart
1:Green
& Salkind: Lesson 40, Exercises 1–4The following helpful tips are numbered 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 1–3The 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
2×2 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.
?2 value ?2(1, N = 130) = 9.83e. Strength of relationship between taking advanced
math classes and level aof parenting2. ———- (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..jpg”>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 Homework1. 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 StudyIt 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, includingthe
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: .psych.washington.edu/writingcenter/writingguides/pdf/stats.pdf”>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).

.jpg”>