SOCI332 Week 8 Final Portfolio Presentation

We finally made it!  Now it is time to share with the class what you have found about your particular topic.  You've worked too hard on this project to only share its completion with your instructor -- sharing with our whole class is a positive and empowering way to end the class. 

Take your Week 7 Final Portfolio Assignment and digest it in a presentation format.  Create a narrated multimedia presentation using either Power Point, Screencast-o-matic, or Prezi.  Remember, narration with audio (not just ppt notes) is necessary.  In essence, your presentations should "play" for us.  The presentation should be no more than 5-10 minutes (about 8-10 slides).  Be sure to provide some background on the topic, discuss your variables, provide figures (tables/charts - frequencies/graphs, crosstabs, tests of significance and measures of association), and conclude by highlighting how your research fits into the existing body of literature on this topic.

Lastly, take the time to view what your classmates have done and leave constructive feedback based on your review.  

   

SOCI332 Week 7 Assignment 3 Final Portfolio Project

Instructions

Final Portfolio Assignment

Overview

One of the most crucial components of this course is developing a research project from conceptualizing a research problem and developing a number of measurement and statistical analysis approaches to bring evidence to bear on the problem. Throughout the class, you created a research study based on publicly available data from the General Social Survey (GSS). You chose data which were representative of your interests and satisfied your research question and hypotheses.

This Assignment meets these course objectives:

CO1: Describe and apply the concepts and logic of elementary statistics.
CO2: Conduct statistical analysis in SPSS (Statistical Package for the Social Sciences).
CO3: Compare and contrast different types of data and the statistics that can be used to analyze them
CO4: Examine the differences between descriptive and inferential statistics and their use in the social sciences.
CO5: Complete and interpret descriptive and inferential statistical data analysis.
CO6: Develop a research project from conceptualizing a research problem and develop a number of complementary design, measurement, and data collection approaches to bring evidence to bear on the problem.
CO7: Form critical interpretations of quantitative research literature in sociology and other social sciences, critically evaluating the quality of research design and evidence in published social research.

Instructions

The Final Portfolio Assignment is where you pull together the research you've been working on the first seven weeks of class. Using your weekly Discussion posts, and the feedback from your classmates and instructor on your posts, construct a 6+ page paper that fully explores your research topic in a way that provides the context and explanation surrounding the analyses provided in the paper. Your project should display you understand what you are writing about holistically, not simply going through the motions.

Citing literature about your research topic, be sure to set the stage for the data and analyses that you present. Briefly describe the General Social Survey as your survey instrument. Provide the questions, verbatim, that were asked in the survey which became the variable which you chose to use. You will also need to include the answer choices for each of them. This portion can be a table if you choose. Share and explain frequency table(s) an histograms or graphs to describe your data. Using the statistical tests you ran each week in class (crosstabs, tests of significance, measures of association), present the tests and your findings. Clearly identify and explain your hypothesis and the five steps of hypothesis testing as they apply to your paper. Explain the results of the statistical tests and pull in some literature to provide context, demonstrating how your results and research fit into the larger body of literature on this topic. Be sure to use proper APA formatting for citations and references. However, you do not need to include an abstract or table of contents. You can find guidance in APA by clicking here to access the Purdue Online Writing Lab.

Because the project is a formal, you should include a title page and reference page. You may organize the paper based on the following headings:

Introduction - Introduce the topic based in current literature (briefly - show why it is important to study). Discuss why you chose the topic and what the purpose of the paper is. Give a brief overview of what you will cover.

Literature Review - Review 3-4 peer-reviewed sources that provide a background on your topic. These sources don't have to specifically address the relationship between your IV and DV, but should address the topic and be somewhat related to your variables.

Methods - Briefly discuss the GSS (information you included in Assignment 1) as your data source. Identify and describe your specific variables, including the name, question, and responses (categories). You may state your hypothesis here, but do not go through the hypothesis testing steps until the next section.

Findings - Begin with a discussion of each variable individually, utilizing your frequency tables and charts/graphs. Then discuss your other analyses in logical order. Crosstabs are your first look at a potential relationship. Next, discuss the steps of hypothesis testing. Include the table of your significance test. Last, discuss the strength and direction of the relationship using measures of association. (Be sure you are thorough here. Include all of your analyses done in the discussions!)

Discussion - Discussion what you learned from the various analyses and draw any conclusions you found. Talk about any further research you think may be needed on your topic.

 

General requirements:

• Submissions should be typed, double-spaced, 1" margins, times new roman 12 pt font, and saved as .doc, .docx, .pdf.
• Use APA format for citations and references
• View the grading rubric so you understand how you will be assessed on this Assignment. 
• Disclaimer- Originality of attachments will be verified by Turnitin. Both you and your instructor will receive the results.
• This course has "Resubmission" status enabled to help you if you realized you submitted an incorrect or blank file, or if you need to submit multiple documents as part of your Assignment. Resubmission of an Assignment after it is grades, to attempt a better grade, is not permitted.

     

SOCI332 Week 6 Discussion Tests of Significance and Measures of Association

This week's main Discussion requires you to respond to the prompts completely and correctly to receive full credit. 

Week 6 Discussion

In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further. During Week 5, we studied tests of significance. In this week's discussion, we will apply these tests of significance to our project variables. We will also run measures of association to determine the strength and direction of the relationship between our variables. As we discussed previously, the levels of measurement of our variables determine which test of significance works for the research project. Here is the guideline: 

1. Before-and-after design and the DV is at I/R level: Dependent Sample T-test

2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square

*Special note for Chi-square: you should have less than 20% of the cells with an expected count of 5 or less. This information is reported automatically, right below the chi-square output table. If your chi-square test fails to meet this requirement, it is necessary to use "recoding" to combining certain answer categories together so the expected counts would increase.  

3. DV and IV are both continuous (interval/ratio) variables: regression

4. Comparison of groups (when IV is categorical - nominal/ordinal and DV is continuous - interval/ratio):

           a. Between 2 groups: Independent Sample T-test

           b. Among 3 or more groups: ANOVA

Why do we need to run tests of significance?

1. They allow us to see if our relationship is "statistically significant." To be more specific, these tests tell us if a relationship observed in a sample, like your research project based on GSS 2016 data set, is generalizable to the population from which this sample was drawn (US adults).
2. Test results reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.

Next, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests. These tests are also specific to the level of measurement of your variables. Here are the guidelines:

1. Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)
1. If it is a 2X2 table: Phi
2. Both DV and IV are ordinal variables: Gamma
3. One variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma
1. One variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.
4. Both DV and IV are I/R variables: Pearson's r

To interpret the output, see attached handout. Keep in mind measures of association is a statistical procedure based on Proportional Reduction of Error (PRE). Thus the format of interpretation will be: Knowing the IV will reduce error in predicting the DV by *%. 

Please note: Don't just say "IV" and "DV" in your explanation. You need to enter your variables names for IV and DV, and replace * for the exact test value from the output. If the value of Lambda is .34, then it will be interpreted as 34%.

****Ok, now it is time for you to try! For this week's discussion, be sure to perform the correct test of significance (choose one) and measure of association (choose one) on your variables for the final project. You can download the class handout attached at the bottom of the page.

This week in the discussion:

I. You will decide which test of significance you will use for your project. Use the guideline above to make your choice.

II. You will use the process for hypothesis testing which outlines five steps:

1. Write your research hypothesis (H₁) and your null hypothesis (H₀).
2. Identify and record your level of significance (alpha): either .05 or .01.
3. Complete the significance test using SPSS. (Include the output of the analysis (table) in your post.)
4. Identify the number under Sig. (2-tail).  This will be represented by "p." Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:
1. If p < or = alpha, than you reject the null hypothesis
5. Determine what to do with your null and explain this to your reader.  Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research.

III. You will decide which measure of association you will use for your project. Use the guideline above to make your choice. Include the output (tabe) in your post. Based on the output, describe the strength and direction of the relationship between the variables. Also explain the PRE.

   

SOCI332 Week 5 Assignment 2

Assignment 2: Tests of Significance

 

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 2018 dataset. The variables are specified in each Mock Study.

c. Go through the five steps of hypothesis testing (below) 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 < or = alpha, then 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.

 

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  (50 points)

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 (ADL) after group therapy than the average for depressed people. More ADL is a positive outcome. The researchers randomly selected 15 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)

 

CLIENT	AFTER THERAPY ADL
A	18
B	14
C	11
D	25
E	24
F	17
G	14
H	10
I	23
J	11
K	22
L	19
M	15
N	17
O	23

 

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 (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.

 

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 10 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)

 

CLIENT	BEFORE THERAPY	AFTER THERAPY
A	11	17
B	7	12
C	10	12
D	13	21
E	11	12
F	12	15
G	9	16
H	8	17
I	13	17
J	12	8

 

 

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 (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)

 

PARTICIPATED IN COUNSELING	DID NOT PARTICIPATE IN COUNSELING
36	38
39	36
41	36
36	32
37	30
35	39
37	41
39	35
42	33

 

 

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 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

39    1

……….

38    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 2018 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 2018 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: Fileà Open Dataà GSS2018.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 Congress (legislative 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%), and what does this mean in regard to this mock study.

 

Variable from GSS 2018 dataset to be used (instructions below):

 

CONLEGIS – confidence in congress
1 = A GREAT DEAL

2 = ONLY SOME

3 = HARDLY ANY

 

 

Step 1: Data managing

 

1. Open a blank SPSS data file: Fileà Open Dataà GSS2018.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 CONLEGIS to "Test Variable list."

·       This procedure instructs SPSS that the chi-square for goodness of fit should be performed on the confidence in congress 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 different 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 Congress and how strongly that person identifies with a specific political party. 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 the observed frequency is significantly different from the expected frequency, and what that means in regard to this mock study. In other words, does political party affiliation effect one's confidence in Congress?

 

Variables from GSS 2018 dataset to be used (instructions below):

 

CONLEGIS – confidence in congress (legislative branch of government)
1 = A GREAT DEAL

2 = ONLY SOME

3 = HARDLY ANY

 

PARTYID – political party affiliation

0 = STRONG DEMOCRAT

1 = NOT STR DEMOCRAT

2 = IND NEAR DEMOCRAT

3 = INDEPENDENT

4 = IND NEAR REPUBLICAN

5 = NOT STR REPUBLICAN

6 = STRONG REPUBLICAN

7 = OTHER PARTY

 

 

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 "PARTYID" to "Column(s)"à use arrow to move "CONLEGIS" 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 2018 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: Fileà Open Dataà GSS2018.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.