Throughout this assignment you will review six mock studies. Follow the step-by-step instructions: a. Mock Studies 1 – 3 require you to enter data from scratch. You need to create a data set for...

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

a. Mock Studies 1 – 3 require you to enter data from scratch. You need to create a data set for each of the three mock studies by yourself. (Refresh the data entry skill acquired in Week 1.)

b. Mock Studies 4 – 6 require you to use the GSS 2016 dataset. The variables are specified in each Mock Study.

c. Go through the five steps of hypothesis testing (as covered in the lesson for Week 4) for EVERY mock study.

d.
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 (alpha) at .05 or .01, based on the mock study. In Mock Study One, 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’ or ‘Asymptotic Sig.’ We will call this “p.”


5. Compare the two and apply the following rule:




1. If “p” is


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.

This assignment is due no later than Sunday of Week 5 by 11:55 pm ET. Save this Word file in the following format: [your last name_SOCI332_A2]. Your spv (SPSS output) file should be labeled [your last name_SOCI332_A2Output].

t-Tests

Mock Study 1: t-Test for a Single Sample (20 points)

1. Researchers are interested in whether depressed people undergoing group therapy will perform a different number of activities of daily living after group therapy than the average for depressed people. 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:
File
à

New
à

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 (numbers listed under AFTER THERAPY - 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 (15 points)

1. 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:
File
à
New
à
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. 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

à
Paired-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 (15 points)

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 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:
File
à

New
à

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 participate 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 (15 points)

Mock study 4: One-Way ANOVA

1. An advertising firm has been hired to assess whether different demographics have different rates of TV watching to help determine their advertising strategy. Using the GSS 2016 data, determine whether hours of tv watched differs by race.

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

As part of Step 5, indicate whether the advertising firm should target each racial group differently (if their habits differ) based on evaluation of the null hypothesis.

Variables from GSS 2016 dataset to be used (instructions below):

RACE – race of respondent
1 = WHITE

2 = BLACK

3 = OTHER

TVHOURS – hours per day watching TV

Step 1: Data managing

1. Open a blank SPSS data file:
File
à

Open Data
à

GSS2016.sav (from wherever you have it saved)

Step 2: SPSS execution

1. Click:
   Analyze
   
   à
   
   Compare Means
   
   à
   
   One-Way ANOVA
   
   à
   use arrow to move TVHOURS to “Dependent Variable list” à use arrow to move RACE to “Factor,” which instructs SPSS to conduct the analysis of variance on the number of activities performed by therapy type.


2. Click:
   Options
   
   à
   
   Descriptive
   (to obtain descriptive statistics).


3. Click:
   Continue


4. Click:
   OK.

Additional question based on Mock Study 4

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

Chi-Square (20 points)

Mock study 5-1:

Chi-Square Test for Goodness of Fit

1. Researchers are interested in whether US adults have different levels of confidence in the President (executive branch) of the federal government.

Following the
five steps of hypothesis testing,
conduct “goodness of fit” chi-square test to determine whether the observed frequencies are significantly different from the expected frequencies at the .01 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 adults in each confidence category is assumed (100%/3=33%). What does this mean in regard to this mock study?

Variable from GSS 2016 dataset to be used (instructions below):

CONFED – confidence in executive branch of federal government
1 = A GREAT DEAL

2 = ONLY SOME

3 = HARDLY ANY

Step 1: Data managing

1. Open a blank SPSS data file:
File
à

Open Data
à

GSS2016.sav (from wherever you have it saved)

Step 2: SPSS execution

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

· This procedure instructs SPSS that the chi-square for goodness of fit should be performed on the confidence in federal government 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 levels of confidence; in other words, SPSS will assume that the proportions of adults in each level are equal.

2. Click
   OK.
   

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

2. Next, researchers categorized the same group from the previous study based on the level of confidence in the federal government and whether that person is of a certain (self-identified) social class. These data are presented below.

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 social class affects one’s confidence in the President.

Variables from GSS 2016 dataset to be used (instructions below):

CONFED – confidence in executive branch of federal government
1 = A GREAT DEAL

2 = ONLY SOME

3 = HARDLY ANY

CLASS – subjective class identification
1 = LOWER CLASS

2 = WORKING CLASS

3 = MIDDLE CLASS

4 = UPPER CLASS

5 = NO CLASS

Step 1: Data managing

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

Step 2: SPSS execution

1. Click:
   Analyze
   
   à
   
   Descriptive Statistics
   
   à
   
   Crosstabs
   
   à
   
   use arrow to move “CLASS” to “Column(s)”à
   
   use arrow to move “CONFED” to “Row(s).” (Recall in crosstab, DV is always in the row and IV 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.

Regression (15 points)

Mock study 6:

Linear Regression

1. Researchers in the field of gerontology are researching the effects of age on mental health. They are using GSS data to gather some preliminary findings.

Following
the five steps of hypothesis testing, conduct a linear regression analysis to determine whether age affects number of poor mental health days at the .05 level of significance. (Clearly list each step).

As part of Step 5, indicate whether there is a significant relationship between age and mental health at the .05 level and what does this mean in regard to this mock study. Should the researchers continue their study?

Variables from GSS 2016 dataset to be used (instructions below):

AGE – age of respondent

MNTLHLTH – Days of poor mental health past 30 days

Step 1: Data managing

2. Open a blank SPSS data file:
File
à

Open Data
à

GSS2016.sav (from wherever you have it saved)

Step 2: SPSS execution

5. Click:
   Analyze
   
   à
   
   Regression
   
   à
   
   Linear
   
   à
   use arrow to move MNTLHLTH to “Dependent list” à use arrow to move AGE to “Independent,” which instructs SPSS to conduct the linear regression on the relationship of age to poor mental health.


6. Click:
   OK.

This assignment is due no later than Sunday of Week 5 by 11:55 pm ET.

Save this file (as a Word file) in the following format: [your last name_SOCI332_A2]. You must also submit an SPSS output file (.spv) labeled [your last name_SOCI332_A2Output].