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: prof.strof@gmail.com—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.