Soc 312: Introduction to Statistics in Sociology
Transcript of Soc 312: Introduction to Statistics in Sociology
01:920:312:01, Spring 2014 Soc 312 syllabus, updated 1/22/2014, page 1
Soc312:IntroductiontoStatisticsinSociology
Lecture: MTh 10:20–11:40am in 219 Beck Hall, Livingston Campus
Lab: Th 12:00–1:20pm, usually in 106J1 Tillett Hall, but sometimes in 111 Beck Hall
Instructor: Andrew Stroffolino
Office Hours: before lecture or by appointment in 110 Davison Hall (Douglass)
Email: [email protected]—put “soc 312” in the subject line. I’ll reply within 48 hours.
Courseoverview
In this course, you will learn to tell stories about quantitative data. I will begin by teaching you how to
describe groups of people—for example, in terms of income, attitudes, or height. I will then teach you
how to do something quite amazing: with access to only a small number of people, you will learn how
to make very accurate statements about much larger groups! Finally, you will learn how to assess
whether the relationship between two variables is weak or strong—for example, weight and frequency
of exercise.
During each “lecture” period, we’ll learn the concepts underlying a particular form of analysis by
looking at a small dataset. “Recitation” will typically entail using computer software (Excel) to analyze a
larger dataset. For this class, you will analyze variables from a nationally representative sample of
people.
This course meets the School of Arts and
Sciences core requirements for Cognitive
Skills and Processes in terms of
“Quantitative and Formal Reasoning” and
“Information Technology and Research.” See
http://sasundergrad.rutgers.edu/core.
Courseobjectives
• Gain the ability to think critically about
quantitative data described in scientific
and media reports
• Learn how to calculate and interpret
basic descriptive and inferential statistics
• Be able to determine when, why, and
how various statistical tests are used
• Be able to analyze data using
spreadsheet software (e.g., Excel)
01:920:312:01, Spring 2014 Soc 312 syllabus, updated 1/22/2014, page 2
Prerequisites
I design lectures under the assumption that you have little or no statistical background. However, you
should know basic math, for example, the Order of Operations: (1) Parentheses, (2) Exponents, (3)
Multiplication and/or Division, and (4) Addition and/or Subtraction (mnemonic tool: please excuse my
dear Aunt Sally). For a quick overview, check out this video (and others) from Khan Academy:
http://tinyurl.com/lxvwz4u. For a more general review of basic math, read the textbook’s “Prologue.”
Grading
Item % Description
In-class
assignments
5 I’ll administer in-class assignments about once a week. You get credit if you submit
something; if you’re absent (unexcused), you don’t get credit. I’ll look over your work
by the next class period, and I’ll post the answers on Sakai. If you’re having trouble
with these assignments, make an appointment to meet with me. Missing one of these
assignments will not affect your grade.
Homework
assignments
30 For each of the six homework assignments, you will apply what you have learned in
lecture and recitation. Emphasis will be placed on your interpretation of results. All
assignments must be submitted electronically on Sakai by 5pm of the due date (see
Homework Schedule below). If your assignment is submitted late, your grade will be
lowered by 10%. Once you submit an assignment, there are no resubmissions. Each
assignment is worth 5% of your final grade.
Midterm
exams
40 Each of the midterm exams will contain approximately 30 multiple-choice questions
and 4 short-answer word problems. All information from the readings and all material
covered during lectures are fair game for the exams. The exams are closed-book, but
I’ll give you all the formulas that you’ll need. As with every other day of class, a
calculator is required. You may not use your phone. Exams are “cumulative” in that
later course material relies on earlier course material. So if you do poorly on the first
exam and do not go back and learn that material, you will do poorly on the next exam.
Make-up exams will only be permitted for emergencies beyond your control. Each of
these exams will be worth 20% of your final grade.
Final exam 25 The third exam follows the same format as the midterms, but may be slightly longer
(e.g., 35 multiple-choice questions).
A: 90–100 B+: 87–89 B: 80–86 C+: 77–79 C: 70–76 D: 60–69 F: < 60
Academic integrity policy
Violating the university’s Academic Integrity Policy is an all-around bad idea. I take integrity very
seriously, and misconduct is remarkably easy for me to detect. All violations of the Policy—for
example, cheating during examinations or plagiarizing others’ work for your assignments—will be
referred to the appropriate authorities and sanctioned accordingly. See
http://academicintegrity.rutgers.edu.
01:920:312:01, Spring 2014 Soc 312 syllabus, updated 1/22/2014, page 3
Requiredmaterials
1) You will need to bring a calculator to class each day. Though any calculator is fine (except cell
phone calculators), I recommend those that let you view multiple entries, like this one:
i. TI-30X IIS 2-Line Scientific Calculator (currently $13 new from Amazon/Walmart/etc.)
2) Healey, Joseph F. Statistics: A Tool for Social Research. (recommended) If you would like to save
money, use a site like http://www.bookfinder.com/ to compare prices from many online retailers.
The ISBN of the current edition is 9781111186364. To save more money, consider buying an older
edition of the book. Aside from updated examples that address things like recent presidential
elections, the stuff that’s inside each edition is pretty much the same. The ISBN of the 8th ed.
(currently $43.00 used on Amazon) is 9780495096559 and the 7th ed. (currently $4.89 used) is
9780534627942.
3) Other materials are under “Resources” of our Sakai site: https://sakai.rutgers.edu/portal.
Attendance
Use the absence reporting website to specify days that you will be absent along with the reason for
your absence. An email will automatically be sent to me. See https://sims.rutgers.edu/ssra. You are
encouraged to send me a separate email to receive any in-class assignments you may have missed.
Appropriateclassroombehavior
Classroom behavior that distracts students and faculty is not acceptable. Such behavior includes using
a cell phone (including texting), surfing the internet, checking email, reading newspapers, listening to
music, leaving early without permission, and making discourteous remarks. Students who do these
things tend to distract other students far more than they realize.
Studentswithdisabilities
If you have any disabilities that you think I should know about, please talk to me as soon as possible. To
verify your eligibility for accommodations, you must register with the Office of Disability Services. See
http://disabilityservices.rutgers.edu.
MicrosoftExcelisnotonmycomputer!WhatdoIdo?
The university has Excel installed in every “computer lab.” Note that not every computer on campus is
part of a “lab.” Lab locations are listed here: http://www.nbcs.rutgers.edu/ccf/main/locations/.
(Alternatively, you can use Excel from home using https://apps.rutgers.edu/novnc/, but be advised
that using the remote interface can be very frustrating.)
Isthereextracredit?
No. You should plan to do well on work that is actually assigned and, if you do poorly on an assignment,
you should identify your errors and aim to do better on later assignments. That’s what learning is
about. If you need help, that’s what I’m about—come to my office hours.
01:920:312:01, Spring 2014 Soc 312 syllabus, updated 1/22/2014, page 4
Courseschedule
Date Topic Reading
1 Thu, Jan 23 course overview
2 Mon, Jan 27 levels of measurement, frequency distributions Ch. 1
3 Thu, Jan 30 frequency distributions Ch. 2
4 Mon, Feb 3 measures of central tendency Ch. 3
5 Thu, Feb 6 measures of central tendency, measures of dispersion Ch. 4
6 Mon, Feb 10 measures of dispersion
7 Thu, Feb 13 probability, the normal distribution, review for exam Ch. 5
8 Mon, Feb 17 examination #1
9 Thu, Feb 20 probability, the normal distribution Ch. 6
10 Mon, Feb 24, sampling distribution, point estimates, confidence
intervals
Ch. 7
11 Thu, Feb 27 Frickel & Vincent
12 Mon, Mar 3 introduction to hypothesis testing, one-sample t-test Ch. 8
13 Thu, Mar 6 one-sample t-test, two-sample t-test Ch. 9
14 Mon, Mar 10 Review
15 Thu, Mar 13 examination #2
Mon, Mar 17 – Thu, Mar 20 SPRING BREAK -- NO CLASSES
16–18 Mon, Mar 24; Thu, Mar 27; Mon, Mar 31 analysis of variance Ch. 10
19–20 Thu, Apr 3; Mon, Apr 7 crosstabulation; chi square test Ch. 11; Ch. 12 (on lambda)
21 Thu, Apr 10 crosstabulation, chi square test, introduction to
spuriousness and statistical control
Ch. 15
22–23 Mon, Apr 14; Thu, Apr 17 correlation, regression Ch. 14
24 Mon, Apr 21 guest speaker Ch. 16
25 Thu, Apr 24 multivariate regression, course wrap-up
26–27 Mon, Apr 28– Thu, May 1 review
28 Mon, May 12 8:00–11:00am examination #3 in regular classroom
Some topics may take a bit more or less time than indicated above. Any changes in dates will be
announced in class. If you miss class, you are responsible for finding out about these changes.
Homeworkschedule
Assignment Due date
1: frequency distributions Wed, Feb 5
2: central tendency, dispersion Wed, Feb 12
3: probability, confidence intervals Wed, Mar 5
4: ANOVA Sun, Apr 6
5: crosstabulation, chi square test Wed, Apr 16
6: correlation, regression Wed, Apr 23
Submit homework to Sakai by 5:00pm.