1 Sociology 360: Statistics for Sociologists I Spring 2010 Instructor: Danielle Berman 3459 Sewell Social Sciences Building 262-7787 [email protected] Lectures: TR 8:00a.m.-9:15a.m. 6240 Social Science Office Hours: Thur. 1:00-3:00 p.m., or by appt. Teaching Assistant: Shane Sharp 8142 Sewell Social Sciences Building [email protected] Office Hours: Mon 10:00am-12pm, or by appt. Labs : 322: Mon 7:45-9:40a.m. (3218 Social Science) 321: Mon 1:20-3:15p.m. (3218 Social Science) Overview: This course introduces methods of empirical social research, and how they are used to assemble, describe, and draw inference from data. Emphasis is on basic but very serviceable methods of statistical analysis for information drawn from surveys or archives. Our coverage of statistical analysis starts simple and gets gradually more involved. We start with numerical and graphical tools to examine distributions of single variables, next move to correlation and regression to describe the relationships between a pair of variables. We also cover the basics of statistical inference for generalizing beyond a sample data. Upon completion of the course, we hope that you will be a more informed and critical reader of academic work, news accounts and advertising materials that present statistical evidence. You should also be able to execute and present elementary statistical analyses on your own. Prerequisites: Sophomore standing and basic algebra skills Required Text and Readings: Moore, Davis S. 2007. The Basic Practice of Statistics. Fourth Edition. New York: W.H.Freeman. (Available at the University Bookstore.) Recommended Texts: Fligner, Michael A. and William I. Notz. 2006. Study Guide for Moore’s the Basic Practice of Statistics, Fourth Edition. New York: W.H. Freeman. (Available at the University Bookstore.) Software Resources: We will do a substantial amount of data analysis this semester with the aid of a software package called Stata. You can access Stata in the Social Science Microcomputer classroom in 3218 Social2 Science or in 4218 Social Science. You will also be able to access Stata remotely from home. The TA will cover how to do this in lab. Course handouts, on-line help files, and instruction in section meetings will teach you how to use Stata gradually. Web Resources: The course website is available through learn@UW. If you enrolled in the course, you can access the site by going to http://learnuw.wisc.edu and entering your NetID and password. Once there, click on the link to SOC360 under “My Madison Courses.” Moore’s text comes with many useful online supplements (http://bcs.whfreeman.com/bps4e). You may find some of them very useful (e.g., statistical applets and data sets). Calculators: You will need a calculator for the homework assignment and exams. If you have, or purchase, a calculator capable of doing “two-variable statistics,” (such as the Texas Instruments TI-36X Solar) you may want to spend some time learning how to take advantage of these capabilities. This will not be covered in class or lab. Requirements: (1) Problem sets Timely practice and repetition are essential to improve your comfort with and abilities in statistical analysis. For this purpose, the course requires a series of problem sets. A new problem set will be assigned most Thursdays and will be due at the beginning of class (8:00 a.m.) on the subsequent Thursday. Homework received after 8:00 a.m. the day it is due will be considered late. (2) Exams One of the important goals of this course is to develop your skills in conducting and interpreting statistical analysis. This goal will be assessed through three non-cumulative exams. (3) Written assignments Another important goal of this course is to develop your skills as an informed and critical consumer of statistical evidence. The first written assignment will provide an opportunity to apply descriptive statistics and graphical display of data for the purpose of critically analyzing statistical claims. It is also important to develop your skills as a producer of social research. The second assignment will require you to apply all the skills you have learned through the course through independent research. Data for both assignments will be provided. (4) Attendance and participation You are expected to attend all lectures. Attendance will be taken. Though this is a lecture class, active participation is encouraged.3 Preparing for Lecture: A good way to prepare for lectures is to read the chapter. You are responsible for reading the entire chapter for each topic, unless indicated otherwise. You will not need to bring your textbook to class. Please bring your calculator. Lecture slides will be made available on the course page prior to lecture. I recommend bringing a print-out of the slides with you to lecture for note-taking. Labs: Labs will consist of: (a) follow-up and elaboration of materials covered in lecture sessions; (b) feedback on prior problem sets; (c) instruction in computing for upcoming problem sets; and (d) questions and review of material covered in lecture sections. Attendance at lab is strongly recommended. Moreover, if your final grade in the class is on the border between two grades, participation in lab can bump you up into the next grade category. Final Grades: Exams 50% (15%, 15%, 20%*) Problem Sets 20% Written Assignments 25% (10%, 15%) Attendance and participation 5% Course Policies: Exam Grades: As a general policy, exams will not be graded on a curve. However, your best exam score will be weighted the heaviest (20%) in calculating your final grade. Make-up Examinations. If you cannot take an exam because of an unavoidable scheduling conflict (e.g., religious holiday, athletic event), you must contact the instructor (not the TA) via email at least 2 weeks prior to the exam date. If you have an emergency that prevents you from taking an exam, contact the instructor as soon as possible. Permission of the instructor is required in order to take a make-up exam. A make-up exam will be scheduled either before or after the original exam date. Be aware that the make-up exam may be different from and more difficult than the original exam. Problem Set Grades: Homework will be graded on a “+,” “”, “-“ system. Exemplary assignments will be given “+”s (those that are virtually entirely correct and well-documented), “”s will be given for good