SOCI 332
Statistics for Social Sciences
Need SPSS software & GSS
Week 1:Choose a topic that you would like to research this term. Use the GSS database to find two variables that would support your topic – one independent variable and one dependent variable. Be sure to include the topic, variable names and description in your post. Then discuss how you hope to explore the variables this term and what you hope to learn.
Example:
Does people’s education level affect their income? Independent variable (IV) is education level – the variable DEGREE. Dependent variable (DV) is income – the variable RINCOM16.
Week 5:Analyzing the methods of peer-reviewed study
Find and read a quantitative peer-reviewed journal article that relates to your topic in which the researchers use existing data (a dataset versus collecting their own data). What information about the dataset do the researchers include? How do they describe their research methods? Which variables do they analyze and why? What are their hypotheses? What statistical analyses so they use?
Explain why discussing the data and methods is important to establish the validity and reliability of the research. Discuss any critiques you have of the Methods/Data section of the article. Are they missing any information that would be useful to the understanding of the research? (Include an APA citation of the article.)
Week 8:your findings
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. SHAPE \* MERGEFORMAT
Take your Week 7 Final Project 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 (including frequency tables/charts), include the steps of hypothesis testing, provide figures (crosstabs, measures of association, and tests of significance) and discuss them, 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.
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Week 2: Frequencies and DescrriptivesPrior to completing this week’s discussion, you must have SPSS rented and downloaded. You must also have the GSS dataset downloaded from the SPSS & GSS Overview and saved to your computer. You will first open SPSS and then open the GSS dataset within SPSS. (See Intro to SPSS.)
You are now going to create and post a frequency table, chart, and descriptives table (central tendency/dispersion) of each of your variables.
Complete the following steps:
- Post a brief explanation of your topic. Include your research question and for each variable – the name, survey question or description, answer categories (yes/no, strongly agree, disagree, etc.), and level of measurement (nominal, ordinal, or interval/ratio)
- Include a frequency table for each of your variables. Explain your outputs in no more than 5 sentences for each variable. Cite numbers in the outputs to support your conclusion. When you cite %, use the % reported in the “valid percent” column.
- Create a chart for each variable, which is a graphic representation of your data. The type of chart (pie, bar, or histogram) is based on a variable’s level of measurement. Explain your outputs for each variable. It is OK if your explanation is similar to (but not the same as) the frequency table interpretation since a chart is a different data presentation on the SAME variable. Cite numbers in the outputs to support your conclusion.
- Describe the measures of central tendency (mean, median, mode) and dispersion (variance, standard deviation) for each of your variables. Based on what you have learned in the readings and lessons this week, identify the best measures for each variable and explain what they tell us. What do these measures summarize for us about the variable’s data?
Copy all of the frequency tables and charts into the discussion window or into a document (PDF, MS Word) and attach to discussion. If your table/chart does not fit to the page, choose “copy special” and then “images” or take a screen shot of the table/chart to copy/past into the window.
Week 3: CrosstabsIn our lessons this week, we discuss the use of crosstabulations (crosstabs) as a preliminary analysis to begin investigating the relationship between the IV and DV. A crosstab creates a “snapshot” of our data. Measures of association help to identify the strength and direction of the potential relationship.
You are now going to create and post a crosstab of your variables and a measures of association table.
Complete the following steps:
- Post a brief explanation of your topic. Include your research question and a broad research hypothesis — that is, the relationship of IV to DV. (For example, educational attainment affects family income in US adults.)
- Run a crosstab on your variables. Be sure to explain your findings, including a description of the table, a calculation of the epsilons, and a discussion of the 10% rule.
- Run the correct measure of association for your variables (Choose one – either Pearson R, Gamma, Phi, Cramer’s V or Lambda). Explain what the output means in terms of strength and direction of the relationship. Interpret Proportional Reduction of Error (PRE) using the following statement: Knowing the IV will reduce error in predicting the DV by *%.
Copy the crosstab and measure of association table into the discussion window or into a document (PDF, MS Word) and attach to discussion. If your table does not fit to the page, choose “copy special” and then “images” or take a screen shot of the table to copy/past into the window.
Special note:
When a variable is continuous (interval/ratio level of measurement), for example age of respondent, we do not run crosstabs directly because it will result in a really spread-out table with lots of zeros and low frequency cells. Such a crosstab does not help us understand the data. The correct way is to reduce the level of measurement to either ordinal level or nominal level (group the numbers into categories) by recoding and then run the crosstab. (Please refer to the Lesson Recoding in SPSS for further information.)
As a reminder, here are the guidelines for choosing your measure of association:
- Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)
- Both DV and IV are nominal variables and it is a 2X2 table: Phi
- Both DV and IV are ordinal variables: Gamma
- One variable ordinal or interval/ratio AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma
- One variable ordinal or interval/ratio AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer’s V.
- Both DV and IV are I/R variables: Pearson’s r
Week 6: test of significanceIn Week 3, we used crosstabs to determine if a potential relationship between two variables is worth examining further. During Week 4, we studied tests of significance. In this week’s discussion, students will apply these tests of significance to their project variables. As we discussed previously, the level of measurement of our variables determine which test of significance works for the research project.
Complete the following steps:
- Post a brief explanation of your topic. Include your research question. Next, begin your 5 steps of hypothesis testing by stating your research and null hypotheses. State your alpha level is .05.
- Run a test of significance on your variables (based on the level of measurement). Copy and paste the appropriate table into the window.
- Identify the two-tailed p value and explain your findings. Is p<alpha? Do you reject or fail to reject the null hypothesis? Does your IV affect your DV?
As a reminder, here is the guideline for tests of significance:
1. IV and DV are BOTH categorical variables (nominal/ordinal): Chi-square
2. IV and DV are both interval/ratio variables: Regression
3. IV is categorical (nominal/ordinal) and DV is interval/ratio:
a. IV has 2 values/groups: Independent Sample T-test
b. IV has 3 or more values/groups: ANOVA
Why do we need to run tests of significance?
- 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 our research project based on GSS 2018 data set, is generalizable to the population from which this sample was drawn (US adults).
- Test results reported under “p” in the SPSS output tell us the probability or likelihood that a relationship observed in the sample is not real, but rather due to factors like a sampling error or chance. We compare this “chance” with alpha (level of significance), commonly set as .05 or .01. If this chance is smaller than level of significance (p<alpha), we can reject the null hypothesis, and keep the research hypothesis. The smaller the p, the lower the possibility for error.
Assignment 1: Learning and applying tests of significanceComplete the following assignment by filling in all requested information. In this assignment, you will review mock studies and analyze data within each study. You will need to CAREFULLY follow the directions outlined in each section of the attached document using SPSS. Some of the studies require you to enter data and some require you to use the GSS data set. You will list the five steps of hypothesis testing for each Mock Study to see how every question should be formatted. You will decide whether to reject or fail to reject the null hypothesis based on the two-tailed p value. Be sure to cut and paste the appropriate SPSS outputs under each problem and interpret the outputs within the context of each mock study. Use a different (legible) color font for your responses.
NOTE: All calculations should be coming from your SPSS. Hand calculation IS not accepted. You are also required to submit the SPSS output file (*.spv) to get credit for this assignment. This .spv file should include ALL your outputs. In other words, continue to save your output file as you conduct each analysis.
General requirements:
- Submissions should be typed, with 1″ margins, Times New Roman 12 pt font (or similar font), and saved as .doc, .docx, or .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 graded, to attempt a better grade, is not permitted.
(see attachment)
Assignment 2:Final project guide to completing studyOverview:
One of the most crucial components of this course is developing a research project from conceptualization to completion. 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. The Final Project: Guide to Completing the Research Study is where you pull together the research you’ve been working on the first six weeks of class.
Instructions:
Complete the following assignment by filling all requested information into the worksheet. You will need to utilize SPSS and the GSS data set provided in class to complete it. Use a different, but legible, color font for your responses. This assignment is intended to help you complete the writing of a quantitative research essay/article, with particular emphasis on the Findings and Conclusion sections.
This assignment is to be completed and submitted no later than the Sunday of Week 7 by 11:55pm ET. It is worth 100 points.
General requirements:
- Submissions should be typed, double-spaced, 1″ margins, times new roman 12 pt font, and saved as .doc, .docx, or .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 realize 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.
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 themCO4: 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.
(See attachment)