SOC 209: STATISTICS FOR SOCIOLOGY
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Lecture:
Section Number: 31247
Room: COB 110
Day: Tuesday & Thursday
Time: 1:30-2:45 PM
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Instructor:
Office:
Office Hours:
E-Mail:
Kyle Dodson
COB 337
Thursday, 11:30 AM- 12:30 PM (or by appointment)
kdodson2@ucmerced.edu
Course Description
Much of our understanding of reality relies on statistics. The media bombard us with statistical
claims about our opinions, consumer habits, economic-well-being, and even our bodies.
Unfortunately, it is easy to misuse statistics to confirm one’s biases instead of making honest
assessments of social processes. Social scientists need a basic foundation in statistics so they can
critically evaluate others’ arguments as well as avoid mistakes when we conduct our own
research.
This course introduces statistical techniques appropriate for answering social science questions.
It is intended to serve as a primer for the two-course sequence in graduate statistics that is
required of sociology graduate students. No prior knowledge of statistics is assumed, but
students must have a good understanding of algebra. If you have never taken a course in algebra
at the high school level or above, you should consider taking one before taking this course. In
addition to reviewing the basics of statistical analysis, this course will also introduce students to
use of computing software for data analysis, primarily with the use of Stata.
We will cover both descriptive and inferential statistics. Descriptive statistics describe or
summarize sets of numbers. Inferential statistics use sample data to make estimates about the
wider population of interest (for example, using surveys to find out which candidate will win an
election, whether or not voters will recall a governor, or what’s the most popular TV show in
America). This course will cover statistics that describe a single variable (e.g. what is the average
income of Americans?) as well as statistics that describe relationships between multiple variables
(e.g. what is the difference in income between men and women?).
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Learning Objectives
To achieve this goal students will learn how to:
1.
Think critically about the causes and consequences of social inequality
2.
Evaluate empirical sociological research
Course Requirements:
Required Text:
Chava Frankfort-Nachmias and Anna Leon-Guerrero, Social Statistics for a Diverse Society.
New York: W. H. Freeman. Thousand Oaks, CA: Pine Forge Press. 6th edition
You are expected to read all assigned readings before they are listed for class. If you have any
questions regarding these readings, please meet with me. You will be responsible for the
material covered in the readings as well as lecture material.
Required Statistical Software:
Stata SE is installed in the sociology graduate computer labs. You can also purchase Stata IC or
Stata SE (the choice is yours) from UCM Software.
Attendance:
I expect all students to attend class, be on time, not to leave early, and be prepared by reading the
assigned material. Also, no makeup exams will be given, except in the gravest of (documented)
emergencies. Also, we will setup times to meet outside of class (probably in the graduate
computer lab) to discuss using Stata. We will arrange these meetings during the first week of
class.
My notes will not be made available to students. Therefore, it might be useful for you to get
the name and email address of at least one classmate so that if you need to miss class you can
obtain a copy of the notes and announcements. There is space to write this contact information
later in this syllabus. I recommend getting this information after our second or third class
meeting.
Course Materials
You should obtain a calculator for exercises we do in and out of class and exams. A cheap
scientific calculator will be sufficient. You should bring your calculator with you to every class
session. You will not be allowed to use cell phone calculators on the tests.
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Exams—We will have three exams during the session. Exam 1 is on October 2; Exam 2 is on
November 6; and the Exam 3 is on December 11. I will provide the necessary formulas so you
do not need to engage in excessive memorization. The exams are semi-cumulative—it will focus
on the material covered since the previous exam but also requires you to use the tools you
learned before then.
I do not give make-up exams, except under the most extreme circumstances. If for some reason
you have to miss an exam, the chances of you being allowed to do a make-up exam increase if
you make arrangements with me before the exam date and you give me proof of the
circumstances that prevent you from taking the exam. If an unplanned emergency prevents you
from taking an exam, you must contact me either by e-mail no later than the day of the exam.
Problem Sets—Problem sets include calculation and interpretation questions, as well as
questions designed to gauge how well you understand the statistical concepts we are working
with. These problems are assigned to ensure that you can perform the statistical analyses
covered in class and to help you refine your interpretation skills. I will hand out problem sets
regularly (generally every week) and you will have approximately one week in which to
complete and return them to me to be graded (note: the due date will be at the top of each
problem set and it is your responsibility to make sure you turn each problem set in to me on or
before the due date). Problem sets are due at the beginning of class on the due date. Problem
sets turned in after the due date will be penalized 10 percentage points for each day past the due
date. Problem sets will not be accepted if they are turned in more than three days after the due
date.
Lab Assignments— To develop your statistical skills and make you more comfortable using
statistical software, I require that you complete three application assignments throughout the
semester. These assignments will involve a combination of hand calculations, analyzing data
using software and interpreting results, as well as presenting statistical information in a variety of
formats. You may consult with other students about these assignments, but each student must
turn in their own assignment with their own output and calculations.
Assignments are due at the beginning of class on the due date. Late assignments will be
penalized 10 percentage points for each day past the due date. I will provide you with each
assignment at least two weeks prior to the due date.
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Grading
Final Grade Breakdown
Exams (3)
Problem Sets (9)
Lab Assignments (3)
Total
Final Grade Cutoffs
A+
97 – 100
C+
A
93 – 96.9
C
A90 – 92.9
CB+
87 – 89.9
D+
B
83 – 86.9
D
B80 – 82.9
DF
30%
40%
30%
100%
77 – 79.9
73 – 76.9
70 – 72.9
67 – 69.9
63 – 66.9
60 – 62.9
<60.0
Computing
You do not need to buy any software to do well in this course. We will be working in a computer
lab for the lab sessions, which means you will need a UC-Merced user id to log on the computers
(see http://it.ucmerced.edu/get-help for information on getting computing accounts). You will
need to have some way of saving your work after lab sessions or when working on your group
project. You can save your work to an external storage device such as a flash drive. We may
also have to make special announcements outside of normal class hours via e-mail, so I strongly
suggest you check your e-mail account daily.
Disability Statement
I am committed to providing assistance to help you be successful in this course. Reasonable
accommodations are available for students with a documented disability. If you have a disability
and may need accommodations to fully participate in this class, please visit the Disability
Services Center. All accommodations must be approved through Disability Services (Kolligan
Library, West Wing Suite 109). Please stop by or call 209-228-6996 to make an appointment
with a disability specialist.
Honor Code
If you plagiarize, or otherwise cheat, on any exam or assignment, you will fail this course and
your transcript will note your violation of the academic honesty policy. Plagiarism involves
intentionally representing someone else’s words or ideas as your own. If you use outside
sources—either in the form of quotes or ideas—you must cite them to indicate where they come
from. Please see or email me if you need help with citations. When in doubt, ask! If you cheat,
or let someone else represent your work as their own, you are in violation of the student code of
conduct. You will fail this course and your failing grade will be identified on your student
transcript as resulting from academic dishonesty. Please consult the office of student life web site
if you require further information: http://studentlife.ucmerced.edu/ (then go to “Student Judicial
Affairs” and look at the “academic honesty policy”). Your enrollment in this course indicates
your willingness to comply with all requirements and policies.
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Class Schedule
Note: This is a tentative schedule. Readings and topics may be adjusted based on how quickly
we cover material. If there are changes to this schedule, you will receive adequate notice. Exam
dates will not change.
Date
Topic
Readings
Part I: Descriptive Statistics
8/28
Syllabus
Introduction
9/2
Chapter 1
Data, Variables, and Causal Inference
9/4
9/9
Chapter 2
Frequency Distributions
9/11
9/16
Chapters 4 and 5
Summarizing Distributions
9/18
9/23
Chapter 3
Presenting Data
9/25
9/30
Catch-Up/Review
10/2
EXAM 1
Part II: Inferences for Univariate Statistics
10/7
Chapter 6
The Normal Distribution
10/9
10/14
Chapter 7
Sampling
10/16
10/21
Chapter 8
Confidence Intervals
10/23
10/28
Chapter 9: 256-270
Univariate Hypothesis Testing
10/30
11/4
Catch-Up/Review
11/6
EXAM 2
Part III: Inferences for Bivariate Statistics
11/11
Chapter 9: 270-284
Bivariate Hypothesis Testing
11/13
11/18
Chapter 10
Cross-Tabulation
11/20
11/25
Chapter 11
The Chi-Square Test
11/27
NO CLASS: Thanksgiving
12/2
Chapter 13
Correlation/Linear Regression
12/4
12/9
Catch-Up/Review
12/11
EXAM 3
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