Question details

The results of your analysis, including the value of the appropriate
$ 15.00

SPSS Homework 7 Instructions

Chi Square

Part 1:

 

Green & Salkind: Lesson 40, Exercises 1–4

 

The 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 1–3

 

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

 

 

 

 

  1. Percentage of female students who took no advanced math classes? 13.1%
  2. Percent of female students who took no advanced math classes when female students were raised by their fathers? 70.0%
  3. Percent of female students raised by their father only?
  4. χ2  value χ2 (1, N = 130) = 9.83
  5. Strength of relationship between taking advanced math classes and level aof parenting

 

  1. ---------- (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.

 

 

  1. 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

 

 

  1. Create a clustered bar graph depicting your results. (2 pts)

 

  1. 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

 

 

 

 

 

 

  1. Paste appropriate SPSS output. (2 pts)
  2. Paste appropriate SPSS graph. (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)

 

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).

 

 

Available solutions