Assignment : Tests of Significance

Throughout this assignment you will review five mock studies. Follow the step-by-step instructions to:   

a.  Enter data from scratch. This assignment DOES NOT use GSS 2012 data set. You need to create a data set for each of the five mock studies by yourself. (Refresh the data entry skill acquired in Week 1.)

b. Go through the five steps of hypothesis testing (as covered in the lesson for Week 6) for EVERY mock study.  

c.  All calculations should be coming from your SPSS. You will need to submit the SPSS output file (.spv) to get credit for this assignment. 

The five steps of hypothesis testing when using SPSS are as follows:

1. State your research hypothesis (H₁) and null hypothesis (H₀).
2. Identify your significance level (.05 or .01). Except for mock study one, where you are required to use BOTH .05 and .01 to test your hypotheses. For the remaining mock studies, you only need to use ONE level of significance (either .05 or .01) as specified in the instructions.
3. Conduct your analysis using SPSS.
4. Look for the valid score for comparison.  This score is usually under 'Sig 2-tail' or 'Sig. 2'.  We will call this "p."
5. Compare the two and apply the following rule:
   1. If "p" is < or = significance level, than you reject the null.
   2. Please explain what this decision means in regards to this mock study. (Ex: will you recommend counseling services?)

Please make sure your answers are clearly distinguishable.  Perhaps you could bold your font or use a different color.

t-Tests  

Mock Study 1: t-Test for a Single Sample

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 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 in the table) obtained after therapy is significantly different from a mean number of activities of 17 that is typical for depressed people. (Clearly list each step).

Test the difference at both the .05 and .01 levels of significance.

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 (.05 and .01).

Data to be entered in SPSS (instructions below)

Step 1: Data managing

 1. Open a blank SPSS data file: Fileà Newà Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by the depressed clients (see above) in the Data View window.

3. In the Variable View window, change the variable name to "ADL." Set the decimals to zero.

Step 2: SPSS execution

a. Click: Analyze à Compare Means à One-Sample T test à use the arrow to move "ADL" to the Variable(s) window on the right.

b. Enter the population mean (17) in "Test Value"

c. Click OK.

Mock Study 2: t- Test for Dependent Means

2. 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 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 the numbers of activities of daily living obtained before and after therapy are statistically significant at .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the researchers should recommend group therapy for all depressed people based on evaluation of the null hypothesis.

Data to be entered in SPSS (instructions below)

Step 1: Managing data

1. Open a blank SPSS data file: FileàNewàData

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by the depressed clients (see above) in the Data View window. Enter the "before therapy" scores in the first column and the "after therapy" scores in the second column.

3. In the Variable View window, change the variable name for the first variable to "ADLPRE" and the second variable to "ADLPOST." Set the decimals for both variables to zero.

Step 2: SPSS execution

a. Click: Analyze à Compare Means àPaired-Samples t-Test à use the arrow to move ADLPRE under "variable 1" inside Paired Variable(s) windowà and then use the arrow to move ADLPOST under "variable 2" inside Paired Variable(s) window.

b. Click OK.

Mock Study 3: t-Test for Independent Samples

3. Six months after an industrial accident, a researcher has been asked to compare the job satisfaction of employees who participated in counseling sessions with those who chose not to participate. The job satisfaction scores for both groups are reported 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 session are statistically different from the scores of employees who chose not to participate in counseling sessions at .01 level of significance. (Clearly list each step).

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. 

Data to be entered in SPSS (instructions below)

Step 1: Data managing

1. Open a blank SPSS data file: Fileà Newà Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities of daily living performed by those who participated/did not participated in the counseling sessions (reported on previous page). Please create two columns. Column one is the test variable, where you enter ALL the 18 scores in the table.

Column 2 is the grouping variable, where you use "1" to indicate if a score is from someone who participated in the counseling sessions; and "0" to indicate if a score is from someone who chose not to participate in the counseling sessions. The data set will look like this in SPSS Data View window:

36    1

49    1

39    0

36    0

3. After data entry, go to Variable View window, change the name of the first variable (test variable) to "ADL" and the second variable (grouping variable) as "group." Set decimals for both variables to zero.

Step 2: SPSS execution

1. Click: Analyzeà Compare MeansàIndependent-Samples T Testà use arrow to move ADL to "Test Variable" à use arrow to move "group" to "Grouping Variable" àwhen two (? ?) appear, click Define Groups. On the next pop up window, enter "1" for "Group 1" and "0" to "Group 2."
2. Click OK.

ANOVA

Mock study 4

4. 15 clients are placed in three different groups. Clients in Group 1 receives 1 hour of therapy every 2 weeks; clients in Group 2 receives 1 hour of therapy every week; and clients in Group 3 receives 2 hours of therapy every week. Their number of daily activities are recorded in the table on the next page.

Use the five steps of hypothesis testing to determine whether the observed differences in the number of activities across three groups are statistically significant at .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the researcher should recommend counseling based on evaluation of the null hypothesis. 

 Data to be entered in SPSS (instructions below)

 Step 1: Data managing

1. Open a blank SPSS data file: Fileà Newà Data

2. In the blank SPSS data file, create your SPSS data set by entering the number of activities performed by the 15 clients. Please create two columns. Column one is the test variable where you enter ALL 15 scores in above table. Column 2 is the grouping variable, where you use "1" for "GROUP 1," "2" for "GROUP 2," and "3" for "GROUP 3." The data set will look like this in SPSS Data View window:  

16    1

15    1

..........

21    2

36    2

..........

24    3

21    3

3. After data entry, go to Variable View window, change the name of the first variable (test variable) to "ADL" and the second variable (grouping variable) to "THERAPY." Set decimals for both variables to zero.

Step 2: SPSS execution

 Click: Analyze à Compare Means à One-Way ANOVA à use arrow to move ADL to "Dependent Variable list" à use arrow to move THERAPY to "Factor," which instruct SPSS to conduct the analysis of variance on the number of activities performed by therapy type.

1. Click: Options à Descriptive (to obtain descriptive statistics).
2. Click: Continue
3. Click: OK.

Additional question based on mock study 4

 Describe the circumstances under which you should use ANOVA instead of t-Tests. Explain why t-Tests are inappropriate in these circumstances.

Chi-Square

Mock study 5-1: Chi-Square Test for Goodness of Fit

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

Following the five steps of hypothesis testing, conduct "goodness of fit" chi-square test to determine whether the observed frequencies in the four cells are significantly different from the expected frequencies at the .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether the observed frequency is significantly different from the expected frequency when equal number of students in each conflict resolution style (20/4=5) is assumed; and what does this mean in regard to this mock study.

Step 1: Data managing

1. Open a blank SPSS data file: Fileà Newà Data

2. In the blank SPSS data file, please create just ONE column. This column stands for frequencies of different types of conflict resolutions. We'll use "1" for "Aggressive," "2" for "Manipulative," 3 for "Passive," and 4 for "Assertive." The data set will look like this in SPSS Data View window:

1

1 (enter "1" for 8 times, since there are 8 observations)

2

2

3

3

4

4

3. After data entry, go to Variable View window, change the name of this variable to "STYLE." Set decimal to zero.

Step 2: SPSS execution

1. Click: Analyze à Non-Parametric Tests à Legacy Dialogs à Chi-Square à use the arrow to move STYLE to "Test Variable list."

• This procedure instruct SPSS that the chi-square for goodness of fit should be performed 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.

1. Click OK.

Mock study 5-2: Chi-Square Test for Independence

7. Next, researchers categorized the same group students in the previous study based on the primary method of conflict resolution used and whether that student had been suspended from school for misbehavior.  These data are presented below.

Conflict Resolution Method

Following the five steps of hypothesis testing, conduct chi-square test for independence at the .05 level of significance. . (Clearly list each step).

As part of Step 5, indicate whether the observed frequency is significantly different from the expected frequency; and what that means in regard to this mock study.

Step 1: Data managing

1. Continue to work on the data set created in Mock Study 5-1: goodness of fit Chi-square test

2.  Add a second column to the data set. This column stands for whether or not a student was suspended from school due to misbehavior. We'll use "1" for "Yes" and "2" for "No." The data set will look like this in SPSS data view:

1     1

1     1

2     1

2     2

3     1

3     2

4     1

4     2

3. After data entry, go to Variable View window, change the name of this new variable to "SUSPEND." Set decimal to zero.

Step 2: SPSS execution

1. Click: Analyze à Descriptive Statistics à Crosstabs à use arrow to move "STYLE" to "Column(s)"à use arrow to move "SUSPEND" to "Row(s)." (Recall in crosstab, IV is always in the row and DV is always in the column.)
2. Click: Statistics à check "Chi-Square."
3. Click: Continue.
4. Click: Cellsà check "Expected."
5. Click: Continue.
6. Click: OK.

Additional question for mock study 5-2

 8. Use SPSS to calculate the measure of association for variable "STYLE" and "SUSPEND." Insert your SPSS output here. Use the concept of "Proportional Reduction of Error" to interpret your output.