Instructor: Phil Ender
Time: Wednesdays 5-9
Room: Moore Hall 2120
Office Hours: Tuesdays 12-1, Wednesdays, 4-5, and by appointment
Primary Special Reader: Jeff Forrest (email@example.com)
Hours: M 12-2, W 3-5, and by appointment
Introduction to Research Design and Statistics is the first course in a three-course sequence in quantitative social science inquiry. The analysis of data sets from a limited number of studies will play an important role in lectures and assignments. This will provide a vehicle for discussing key aspects of research design, and for illustrating the application of widely-used statistical techniques.
Initially, we will focus heavily on data collected from two senior high schools in the Los Angeles area. We will take a careful look at the characteristics of the students at these two schools, their performance on norm-referenced tests, and their performance in selected academic subjects. In addition, we will discuss the inferences which may be made from the data, develop appropriate questions for further inquires, and consider the design of studies to respond to these inquires.
A fundamental design issue that we will discuss and continue to re-visit throughout the course is that of anticipating and trying to control for possible confounding variables. Next we will analyze the data from the two schools using various graphical techniques and numerical summaries in order to gain a sense of the kinds of students included in the study (their backgrounds and the like), to examine the comparability of the students in the two schools, and to compare the students in the two schools with respect to math and language outcomes. We will then try to interpret and discuss the soundness of our conclusions in light of the information available.
The foundations of statistical inference are the focus of the last five weeks or so of the course.
Agresti, A. & Finlay, B. (1997). Statistical methods for the social sciences, 3rd ed. Upper Saddle River, New Jersey: Prentice Hall.
Jaeger, R. (1990). Statistics: A spectator sport, 2nd ed. Newbury Park, CA: Sage. (Not required but an excellent, gentle introduction to statistics)
The Stata Computer Module is important not only for course work in the Intro course but it also constitutes the basis for the more advanced computer work and data analysis in Linear Statistical Models (Regression and Analysis of Variance).
World Wide Web
Course information, including assignments, datasets, examples, help sheets, computer printouts, and notes are available over the Internet on the World Wide Web at the following URL: http://www.philender.com/courses/intro/
There will be an in-class mid-term and an in-class final examination. Both examinations will be open-book: you can refer to your notes, your textbook or any other written materials.
There will be four computer data analysis assignments to be completed out-side of class time.
The mid-term and final examinations will each count 30%. The four assignments will each count 10%.
Special Readers are assigned by the Department of Education to the Social Research Methodology Division (SRM) to assist students in SRM courses. This assistance covers explanations of concepts and procedures, help with assignments and computer runs, and review for examinations. Readers are assigned to particular courses and their office hours are listed on the door of Moore Hall 2005B. These are the times they are available to help you. In addition, you may use any other "on duty" Reader to receive assistance when your class Reader is "off duty" or tied up with other students. Please do not ask Readers for help when they are not on duty.
Classroom lecture, discussion and demonstration is very good when it comes to covering the vocabulary of research and statistics. How it is not nearly as good when it comes teaching the actual data analyses. Data analysis is "best" learned by doing. Learning data analysis has more in common with learning to play a musical instrument than it does with learning history or psychology. Not amount of discussion makes one a better musician, only practice can do this. Therefore, we will provide numerous opportunities to practice data analysis skills.
Topics from the Textbooks
Intro Home Page
Phil Ender, 7/15/05, 5Oct99