01:920:312:01, Spring 2014 Soc 312 syllabus, updated 1/22/2014, page 1 Soc 312: Introduction to Statistics in Sociology 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. Course overview 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. Course objectives • 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)
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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