Sociology 3112-001
Social Statistics
Fall 2017
University of Utah
Instructor: Tom Quinn, PhD
Office: BEHS 312
Office Hours: TBA
Teaching Assistant(s): TBA
So what’s this class all about, anyway?
This course introduces the basic concepts of data analysis and statistical computing, both increasingly used in the social sciences and the humanities. The emphasis is on the practical application of quantitative reasoning, visualization, and data analysis. The goal is to provide students pragmatic tools for assessing statistical claims and conducting their own basic statistical analyses. Topics covered include basic descriptive measures, measures of association, sampling and sample size estimation, and simple linear regression. Assignments are based on real-world data and problems in a wide range of fields in the social sciences and humanities, including psychology, sociology, education, and public health.
Gen Ed
Successful completion of SOC 3112 will satisfy the following University of Utah general education requirements: QB, and QI.
In fulfillment of the QB-Quantitative ReasoningQI-Quantitative Intensive requirements, the course involves the calculation and interpretation of statistics. Specifically, this class is designed so that students:
- Explain, calculate, and interpret descriptive statistics including: basic terminology, scales, notations, frequency distributions, measures of central tendency, measures of dispersion, and the normal distribution.
- Read and analyze basic charts and graphs, contingency tables, and SPSS output results;
- Explain the logic of hypothesis testing in inferential statistics;
- Explain, calculate, and interpret inferential statistics including t-tests, chi-square, ANOVA, correlation, and regression;
- Identify and apply the correct statistical technique to a research question;
- Use computer technology to compute descriptive and inferential statistics; and
- State several examples of how statistics are used as a tool in the “real world” by social scientists to analyze outcomes of interest
Course requirements and grading
Class attendance is an essential component of success in this course. Because we’ll be going over so much material in such a short amount of time, missing even one class could be detrimental to your grade. Your final grade will be based on the following: exams (50 percent), homework (15 percent), group quizzes (10 percent), labs (15 percent) and a final research paper (10 percent). I do not, under any circumstances, accept late work without prior approval. My grade breakdown is as follows:
A94%-100%
A- 90%-93.9%
B+87%-89.9%
B84%-86.9%
B-80%-83.9%
C+77%-79.9%
C 74%-76.9%
C- 70%-73.9%
D+ 67%-69.9%
D 64%-66.9%
D- 60%-63.9%
E 0%-59
Exams
There will be three exams over the course of the semester. Each exam will consist of a combination of short answer questions and calculations and will cover concepts addressed in class and in assigned readings. Each exam will be worth approximately 17 percent of your final grade.
Homework
There will be a total of six homework assignments, the purpose of which is to prepare you for the abovementioned exams. These assignments are graded on a credit/no credit basis, and each assignment will be worth approximately 2.5 percent of your final grade.
Group Quizzes
We will conclude each class with a quiz that is to be completed in groups of 3-5 students. While graded, these quizzes are primarily designed to serve as an opportunity for you to assess your understanding of the material covered in class that day. Each quiz will be worth approximately 1-2 percent of your final grade.
Labs
The lab section of this course is designed to teach you to use a data analysis software package called SPSS. There will be a total of seven lab assignments, and each will be worth approximately 1 percent of your final grade. Lab assignments will be graded on a credit/no credit basis.
Final Paper
You will be required to complete a final research paper, which will allow you the opportunity to demonstrate your mastery of SPSS. An exquisitely detailed rubric for this paper is available on Canvas. This paper will account for 10 percent of your final grade.
Can I, like, get any extra credit?
Yes. You may earn extra credit by bringing in newspaper and/or journal articles that incorporate any of the topics we go over in class. I reserve the right to assess how much extra credit is awarded for each article. Additional extra credit will be given for instances where you can point out mistakes made by the author(s). Expect to receive about five to 10 points per article, and be aware that I will only allow extra credit to “bump your grade” by one letter grade. That means you can go from a C- to a C or a B to a B+, but you can’t go from a D to an A based solely on extra credit.
Course materials
You will need a calculator with a square root function. It doesn’t need to be anything fancy, but please remember to bring it to class.
I will provide online notes as well as links to videos, websites, etc. that will be useful in furthering your understanding of the material discussed in class. I also highly recommend that you purchase Social Statistics for a Diverse Society by Chava Frankfort-Nachmias and Anna Leon-Guerrero. You can get a copy of the 2005 edition (which is my personal favorite) on Amazon or half.com for about a dollar. Please don’t go out and spend $100 on the new version. The older ones are almost identical.
My advice to you
Many students find the material in this course challenging. Having said that, I am confident that every student is capable of succeeding in this course provided he or she is willing to put in the necessary effort. If you start falling behind or feeling overwhelmed, please talk to me. I am more than happy to meet with you outside of class to answer any questions that you might have. Be aware, however, that “cramming” is not an effective strategy for success in this course. If you wait until the night before an exam to talk to me, you will probably be disappointed in your grade (I’m not saying it can’t be done; I’m merely saying that those who have done it successfully are few and far between).
What happens if I cheat?
Per University of Utah regulations (Policy # 6-400), “A student who engages in academic misconduct, as defined in Part I.B. and including, but not limited to, cheating, falsification, or plagiarism, may be subject to academic sanctions including but not limited to a grade reduction, failing grade, probation, suspension or dismissal from the program or the University, or revocation of the student's degree or certificate. Sanctions may also include community service, a written reprimand, and/or a written statement of misconduct that can be put into an appropriate record maintained for purposes of the profession or discipline for which the student is preparing.”Please refer to the Student Code for full elaboration of student academic and behavioral misconduct policies (
What do I do if have a learning disability or need other accommodations?
Americans with Disabilities Act (ADA): The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities. If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD). CDS will work with you and the instructor to make arrangements for accommodations. All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services.
Addressing Sexual Misconduct
Title IX makes it clear that violence and harassment based on sex and gender (which includes sexual orientation and gender identity/expression) is a Civil Rights offense subject to the same kinds of accountability and the same kinds of support applied to offenses against other protected categories such as race, national origin, color, religion, age, status as a person with a disability, veteran’s status or genetic information. If you or someone you know has been harassed or assaulted, you are encouraged to report it to the Title IX Coordinator in the Office of Equal Opportunity and Affirmative Action, 135 Park Building,801-581-8365, or the Office of the Dean of Students, 270 Union Building,801-581-7066. For support and confidential consultation, contact the Center for Student Wellness, 426 SSB,801-581-7776. To report to the police, contact the Department of Public Safety, 801-585-2677(COPS).
The Fine Print
Some of the readings, lectures, films, or presentations in this course may include material that conflicts with the core beliefs of some students. Please review the syllabus carefully to see if the course is one that you are committed to taking.
Other policies of which you should be aware:
- I do my absolute best to respond to emails within 24 hours, though additional time may be required if your query requires considerable thought and/or a lengthy explanation. Or if you email me on a Friday night.
- With the previous point in mind, I do not respond to emails within 24 hours of exam or assignment due dates. Any questions or requests for clarification should be made well in advance. In other words, you can be the kind of student who requires a lot of help from the instructor (and that's totally fine), or you can be the kind of student who leaves everything until the last minute (and that's also fine), but you cannot be both simultaneously.
- I do not accept late work without prior approval (I know I already mentioned that, but it's worth repeating).
- All assignments and exams must be picked up within six weeks of the end of the semester. After six weeks, any student submissions that have not been claimed will be shredded and subsequently recycled.
- I reserve the right to amend this document at any time and for any reason.
Course Schedule
Date / Topic / Readings / To-Do List8/22/17 / Class Intro and Syllabus / None / Download and Install Citrix Receiver; ensure access to remote lab
8/24/17 / Statistics: Why Bother? / “How Target Figured Out a Teen Girl Was Pregnant Before Her Father Did” / Seriously, make sure you can access the lab and whatnot
8/29/17 / The What and Why of Statistics: Terminology, Usage, etc. / The Basics
Chapter 1: The What and Why of Statistics / Final warning: you must resolve any technology-related issues this week...OR ELSE!
8/31/17 / NO CLASS—FOOTBALL / TBA / Online Quiz
9/5/17 / Frequency Distributions / Frequency Distributions
Chapter 2: Frequency Distributions
9/7/17 / Graphic Presentation / Chapter 3: Graphic Presentation / Lab #1 due by midnight on Friday, September 8, 2017.
9/12/17 / Measures of Central Tendency / Measures of Central Tendency
Chapter 4: Measures of Central Tendency
9/14/17 / Measures of Variability / Measures of Variability
Chapter 5: Measures of Variability / Lab #2 due by midnight on Friday, September 15, 2017
9/19/17 / Summary and Review / None / Prepare yourself for Exam #1
9/21/17 / EXAM #1—YOU MAY USE ONE PAGE OF NOTES AND A CALCULATOR / None / Turn in Homework #1 and #2
Lab #3 due by midnight on Friday, September 22, 2017
9/26/17 / Introduction to Inferential Statistics / Freakonomics, Chapter 1
9/28/17 / The Normal Distribution / The Normal Distribution
Chapter 6: The Normal Distribution (5th edition and later)
Chapter 9: The Normal Distribution (4th edition)
10/3/17 / Sampling and the Sampling Distribution / The Sampling Distribution and the Central Limit Theorem
Chapter 7: Sampling and Sampling Distributions (5th edition and later)
Chapter 10: Sampling and Sampling Distributions (4th edition)
10/5/17 / Confidence Intervals / Confidence Intervals
Chapter 8: Estimation (5th edition and later)
Chapter 11: Estimation (4th edition) / Lab #4 due by midnight on Friday, October 6, 2017
10/10/17 / NO CLASS—FALL BREAK
10/12/17
10/17/17 / Introduction to Hypothesis Testing / Hypothesis Testing and the t Distribution
Chapter 9: Testing Hypotheses (5th edition and later)
Chapter 12: Testing Hypotheses (4th edition)
10/19/17 / More Hypothesis Testing / None / Lab #5 due by midnight on Friday, October 20, 2017
10/24/17 / Summary and Review / None
10/26/17 / EXAM #2—YOU MAY USE ONE SHEET OF NOTES AND A CALCULATOR / Turn in Homework #1 and #2
Lab #6 due by midnight on Friday, October 27, 2017
10/31/17 / Bivariate Tables / Bivariate Tables
Chapter 10: Relationships Between Two Variables (5th edition and later)
Chapter 6: Relationships between two variables (4th edition)
11/2/16 / The Chi-Square Test / Chi Square
Chapter 11: The Chi Square Test (5th edition and later)
Chapter 7: The Chi Square Test (4th edition) / Lab # 7 due by midnight on Friday, November 3, 2017
11/7/17 / Measures of Association for Nominal and Ordinal-Level Variables / Lambda
Gamma
11/9/17 / Bivariate Regression / Regression
Chapter 13: Regression and Correlation (5th edition and later)
Chapter 10: Regression and Correlation (4th edition) / Lab #8 due by midnight on Friday, November 10, 2017
11/14/17 / More Bivariate Regression / R-square and R
11/16/17 / Even More Bivariate Regression / None / Lab #9 due by midnight on Friday, November 17, 2017
11/21/17 / Topic TBA / TBA
11/23/17 / NO CLASS—THANKSGIVING BREAK
11/28/17 / Analysis of Variance (ANOVA) / ANOVA
Chapter 14: Analysis of Variance (5th edition and later)
11/30/17 / Summary and Review
12/5/17 / EXAM #3—YOU MAY USE ONE SHEET OF NOTES AND A CALCULATOR / Turn in homework assignments #5 and #6
Lab #10 due by midnight on Friday, December 8, 2017