Creating Scatter Diagrams and More

Review and follow the steps in your text and you may want to keep SPSS Statistics 21 Brief Guide handy just

in case.

1a.

The following have been prepared so that data sets B through D are slightly modified versions of data set

A. Make scatter diagrams and figure the correlation coefficients for each data set.

DATA SET A

X

Y

1

1

2

2

3

3

4

4

5

5

1b.

DATA SET B

X

Y

1

1

2

2

3

3

4

5

5

4

DATA SET C

X

Y

1

5

2

4

3

3

4

2

5

1

DATA SET D

X

Y

1

1

2

4

3

3

4

2

5

5

Discuss how and why the correlations change.

Correlations

Review the steps in your text and you may want to keep SPSS Statistics 21 Brief Guide handy just in case.

2.

Enter the following data into SPSS. Determine the correlation between hours of studying and grade point

average in these honor students. Copy and paste the results into this document. Explain your results.

Hours of Studying

23

12

15

14

16

21

14

11

18

9

Chi-Square

SPSS instructions:

Chi-Square Test for Goodness of Fit:

Open SPSS

GPA

3.95

3.90

4.00

3.76

3.97

3.89

3.66

3.91

3.80

3.89

Remember that SPSS assumes that all the scores in a row are from the same participant. In the study presented in #1,

there are 20 students, some of whom have been suspended for misbehavior. The primary conflict-resolution style

used by each student is also entered. [Ignore the first variable in this analysis.]

When you have entered the data for all 20 students, move to the Variable View window and change the first variable

name to SUSPEND and the second to STYLE. Set the number of decimals for both variables to zero.

Click Analyze Non-Parametric Tests Chi-Square

Click the variable STYLE and then the arrow next to the box labeled Test Variable List to indicate that the chisquare for goodness of fit should be conducted on the conflict-resolution style variable.

Note that All categories equal is the default selection in the Expected Values box, which means that SPSS will

conduct the goodness of fit test using equal expected frequencies for each of the four styles, in other words, SPSS

will assume that the proportions of students each style are equal.

Click OK.

Chi-Square Test for Independence:

Open SPSS

For #2, you need to add the variable SUSPEND to the analysis. Remember that in this problem, we are interested

in whether there was an association between conflict-resolution style and having been suspended from school for

misbehavior. Since the analysis will involve two nominal variables, the appropriate test is a chi-square test for

independence.

Click Analyze Descriptive Statistics Crosstabs

Since SUSPEND is already selected, click the arrow next to the box labeled Rows.

Click the variable STYLE and click the arrow next to the box labeled Columns.

Click Statistics and click the box labeled Chi-Square.

Click Continue.

Click Cells and click the box labeled Expected.

Click Continue.

Click OK.

1.

The following table includes the primary method of conflict resolution used by 20 students.

Method

N of Students

Aggressive

8

Manipulative

2

Passive

2

Assertive

8

a.

b.

2.

Following the five steps of hypothesis testing, conduct the appropriate chi-square test to determine

whether the observed frequencies are significantly different from the frequencies expected by change

at the .05 level of significance. Clearly identify each of the five steps.

Explain your response to some who has never had a course in statistics.

Next, researchers categorized the students based on the primary method of conflict resolution used and

whether the student had been suspended from school for misbehavior. These data are presented below.

Suspended

Yes

No

Total

Aggressive

7

1

8

Method

Manipulative

Passive

1

1

1

1

2

2

Assertive

1

7

8

Total

10

10

20

a.

Following the five steps of hypothesis testing, conduct the appropriate chi-square test to determine

whether the observed frequencies are significantly different from the frequencies expected by change

at the .05 level of significance. Clearly identify each of the five steps.

b.

Calculate the effect size.

c.

Explain your response to someone who has never had a course in statistics.

Computing z-Scores Using SPSS

Using the data below:

1.

Determine the z-score that corresponds to each teachers salary and enter them in the table below.

(Follow the steps on the second page).

The following data are from a survey of high school teachers.

SALARY

SEX

35,000

Male

18,000

Female

20,000

Male

50,000

Female

38,000

Male

20,000

Female

75,000

Male

40,000

Female

30,000

Male

22,000

Female

23,000

Male

45,000

ZSALARY

Female

Follow the instructions below. For salary be sure to use scale for measure (and you will be entering the actual

number so no need for values); sex is a nominal variable (Male= 1, Female=2).

In SPSS, we compute z-scores via the Descriptives command.

After you enter the data above, click Analyze, then Descriptive Statistics, then Descriptives this will take you to

the dialog box for descriptives.

In the bottom-left corner you will see a check box labeled Save standardized values as variables, check this box

and move the variable SALARY into the right-hand blank. Then click OK to complete the analysis. You will see the

standard output from the Descriptives command. Notice that the z-scores are not listed. SPSS inserts them into the

data window as a new variable (ZSALARY). Copy and paste your results to this document.

2.

Write a brief (but thorough) analysis of what these z-scores say about each teachers salary.

Crosstabs

For this assignment you will be using the data contained in the following file (you can find it under Resources)

soci332_dataset.sav

The Crosstabs command produces frequency distributions for multiple variables. This command is useful for

describing samples where the man is not useful (that is, nominal or ordinal scales) and as a method for getting a feel

for your data.

To run crosstabs:

Click Analyze, then Descriptive Statistics, then Crosstabs. A dialog box will appear with your variables on the

left-hand side and a Row(s) box, Column(s) box, and Layer 1 of 1 box. Move the variable SEX to the Row(s) box,

and the ANY OTHER VARIABLE YOU WANT (or use another attitude-variable that interests you) to the

Columns(s) box. [If you wanted to analyze more than two variables, you would enter the third, fourth, fifth, etc., in

the Layer 1 of 1 box].

Click on the Cells button in the bottom of the dialog box. This button allows you to specify percentages and other

information that you would like from each combination of values. Once you click on Cells, another dialog box

appears, select Observed under Counts; Row, Column, Total under Percentages then click on Continue. You will

return to the Crosstabs dialog box, where you will click OK.

Assignment:

1.

Your assignment is to run at least 5 crosstabs, copy and paste them to this document and briefly explain

each of them.

Single Sample & Dependent Samples t Tests

SPSS instructions: (For more details, check the links provided under Course Materials in the Course

Overview Folder (under Lessons).

t Test for a Single Sample:

Open SPSS

Enter the number of activities of daily living performed by the depressed clients studied in #1 in the Data View

window.

In the Variable View window, change the variable name to ADL and set the decimals to zero.

Click Analyze Compare Means One-Sample T test the arrow to move ADL to the Variable(s) window.

Enter the population mean (14) in the Test Value box.

Click OK.

t Test for Dependent Means:

Open SPSS

Enter the number of activities of daily living performed by the depressed clients studied in Problem 2 in the Data

View window. Be sure to enter the before therapy scores in the first column and the after therapy scores in the

second column.

In the Variable View window, change the variable name for the first variable to ADLPRE and the variable name

for the second variable to ADLPOST. Set the decimals for both variables to zero.

Click Analyze Compare Means Paired-Samples T Test the arrow to move ADLPRE to the Paired

Variable(s) window ADLPOST and then click the arrow to move the variable to the Paired Variable(s)

window.

Click OK.

Review the five steps of hypothesis testing and complete the following problems. Be sure to cut and past the

appropriate result boxes from SPSS under each problem.

1.

Researches are interested in whether depressed people undergoing group therapy will perform a different

number of activities of daily living after group therapy. The researchers have randomly selected 12

depressed clients to undergo a 6-week group therapy program.

Use the five steps of hypothesis testing to determine whether the average number of activities of daily

living (shown below) obtained after therapy is significantly different from a mean number of activities of

14 that is typical for depressed people. (Clearly indicate each step).

Test the difference at the .05 level of significance and, for practice, at the .01 level (in SPSS this means you

change the confidence level from 95% to 99%).

In Step 2, show all calculations.

As part of Step 5, indicate whether the behavioral scientists should recommend group therapy for all

depressed people based on evaluation of the null hypothesis at both levels of significance and calculate the

effect size.

CLIENT

A

B

C

D

E

F

G

H

I

J

K

L

2.

AFTER THERAPY

17

15

12

21

16

18

17

14

13

15

12

19

Researchers are interested in whether depressed people undergoing group therapy will perform a different

number of activities of daily living before and after group therapy. The researchers have randomly selected

8 depressed clients in a 6-week group therapy program.

Use the five steps of hypothesis testing to determine whether the observed differences in numbers of

activities of daily living (shown below) obtained before and after therapy are statistically significant at the .

05 level of significance and, for practice, at the .01 level. (Clearly indicate each step).

In Step 2, show all calculations. As part of Step 5, indicate whether the researchers should recommend

group therapy for all depressed people based on evaluation of the null hypothesis at both levels of

significance and calculate the effect size.

CLIENT

A

B

C

D

E

F

G

H

BEFORE THERAPY

12

7

10

13

9

8

14

11

AFTER THERAPY

17

15

12

21

16

18

17

8

The t Test for Independent Samples

SPSS instructions to run the t Test for Independent Samples: (For more details, check the links provided

under Course Materials in the Course Overview Folder (under Lessons).

Once you have entered the data, click on Analyze, then on Compare Means, and then click on IndependentSamples T Test

A dialog box will appear, with your variables (student, condition, score) on the left. Your options are (a) move one

or more variables into the Test Variable(s) box to select your dependent variables(s) and (b) move one of your

variables into the Grouping Variable box to select the independent variables (or identify the groups to be

compared).

Make ? the dependent variable by moving it to the Test Variable(s) box. Then make ? your independent

variable by moving it to the Grouping Variable box. Now, the Define Groups button is functioning, click on

Define Groups and another dialog box appears. Here you must specify the two values of the condition variable that

represent the two groups you are comparing. Click in the box next to Group 1 and type the number 1, then click in

the box next to Group 2 and type the number 2. Now you can click Continue to return to the Independent-Samples

T Test dialog box, and click on OK to run the analysis.

1.

Six months after an industrial accident, a researcher has been asked to compare the job satisfaction of

employees who participated in counseling sessions with the satisfaction of employees who chose not to

participate.

The scores on a job satisfaction inventory for both groups are listed in the table below.

Use the five steps of hypothesis testing to determine whether the job satisfaction scores of the group that

participated in counseling are statistically higher than the scores of employees who did not participate in

counseling at the .01 level of significance.

In Step 2, show all calculations.

As part of Step 5, indicate whether the researcher should recommend counseling as a method to improve

job satisfaction following industrial accidents based on evaluation of the null hypothesis and calculate the

effect size.

PARTICIPATED IN COUNSELING

36

39

40

36

38

35

37

39

42

2.

DID NOT PARTICIPATE IN COUNSELING

37

35

36

33

30

38

39

35

32

A researcher is interest in the effect of exercise on the perceptions of well-being among older. The

researcher identified 30 residents of a retirement community and divided them into groups of 15 residents.

Both groups were encouraged to walk at least 20 minutes per day. One group, however, also participated in

a structured exercise program that emphasized flexibility. After 6 weeks, the behavioral scientist mailed

questionnaires to the 30 residents. Responses to an item asking residents to rate their perceptions of their

health on a 10-point scale on which 1 indicated very unhealthy and 10 indicated very healthy are

presented in the table that follows.

Use the five steps of hypothesis testing to determine whether the observed differences in health ratings of

the two groups are statistically significant at the .05 level of significance.

In Step 2, show all calculations.

As part of Step 5, indicate whether the researcher should recommend exercise as a method to improve

perceptions of health among older adults based on evaluation of the null hypothesis and calculate the effect

size.

WALKING AND FLEXIBILITY

5

6

6

4

9

4

7

9

6

7

9

7

4

9

8

Analysis of Variance

SPSS instructions:

Open SPSS

WALKING ONLY

2

3

4

3

6

7

7

6

7

4

6

Analyze the data for #1. Remember that SPSS assumes that all the scores in a row are from the same participant. In

this study, there are 15 participants divided into three groups of five. Therefore, each of the 15 participants will be

described by two variables, type of therapy and the number of activities of daily living performed.

If 1 represents the group receiving individual therapy for 1 hour every 2 weeks, 2 represents the group receiving

1 hour of individual therapy each week, and 3 indicates the group receiving 2 hours of individual therapy each

week, the first participant will be described by entering 1 in the top cell of the first column in the Data View

window and 16 in the top cell of the second column to indicate that the participant underwent 1 hour of therapy

every 2 weeks and performed 16 activities of daily living. The second participant will be described by 1 and 15,

and the third by 1 and 18.

When the two variables have been entered for the five participants in this group, repeat the process for participants

who underwent 1 hour of individual therapy each week, using 2 to describe their therapy group. When the two

variables for the five participants in this group have been entered, repeat the process for Group 3, entering 3 in the

first column. In the Variable View window, change the first variable name to THERAPY and the second to

ADL and set the decimals for both to zero.

Click Analyze Compare Means One-Way ANOVA Since THERAPY is already selected, you can click

the arrow to move the variable to the Factor window. Select ADL and click the arrow to move the variable to the

Dependent List window, which instruct SPSS to conduct the analysis of variance on the number of activities

performed.

1.

Keep in mind that the clients in Group 1 will receive 1 hour of therapy every 2 weeks, the clients in Group

2 will receive 1 hour of therapy every week, and the clients in Group 3 will receive 2 hours of therapy

every week.

Use the five steps of hypothesis testing to determine whether the observed differences in the number of

activities in the following table performed by the three groups are statistically significant at the .05 level of

significance. Clearly indicate each of the five steps.

Calculate the effect size for the study. Explain your results.

CLIENT

1

2

3

4

5

2.

GROUP 1

16

15

18

21

19

GROUP 2

21

20

17

23

19

GROUP 3

24

21

25

20

22

A researcher interested in the relationship between student perception of the probability of success in a

statistics course and student motivation has administered an inventory designed to assess motivation in 18

students.

The students have been divided into groups as follows: Students in Group 1 believe they are highly likely

to succeed in the course, students in Group 2 believe they have an intermediate probability of success, and

students in Group 3 believe they have little chance of success.

Use the five steps of hypothesis testing to determine whether the observed differences in level of

motivation in the following table are statistically significant at the .05 level of significance. Clearly indicate

each of the five steps.

Calculate the effect size for the study. Explain the results of the hypothesis-testing procedure to someone

who is familiar with the t test for independent means, but not with analysis of variance.

SUBJECT

1

2

3

4

5

6

3.

GROUP 1 (HIGH)

9.0

8.5

6.5

7.0

8.0

5.5

GROUP 2 (INTERMEDIATE)

3.5

5.5

6.5

3.5

4.5

7.0

GROUP 3 (LOW)

4.5

5.5

6.5

8.0

5.5

6.0

Due to the increasing number of trails involving testimony by behavioral scientists, a professional

organization of behavior scientists asked judges, attorneys, jurors, and law enforcement officials to use a

10-point scale to rate the effect of such testimony on trial outcomes.

The results are presented in the table below. Use the five steps of hypothesis testing to determine whether

the observed differences in effectiveness ratings are statistically significant at the .01 level of significance.

Clearly indicate each of the five steps.

Calculate the effect size for the study. Explain your results.

CATEGORY

Judges

Attorneys

Jurors

Law Enforcement

N

6

6

6

6

M

7.00

5.83

7.83

3.00

S2

1.99

1.37

1.37

3.61