CREDIT HOURS: 3	INSTRUCTOR: Yu-Wen Chen
TIME: Tuesday, 9:10-12:10	OFFICE PHONE: 33661259
ROOM: Social Work 209	OFFICE: 408

I. Course Domain
The major purpose of this course is to teach multivariate analyses, with a major focus on multiple regressions. A thorough comprehension of multiple regressions is important to understand and to conduct the empirical studies with quantitative approaches. Students are required to have some basic knowledge of introductory statistics. This course will start with reviews of elementary statistical concepts to refresh students' memory. A great proportion of this course will focus on teaching both theoretical and technical aspects of regressions. This course will also demonstrate how multiple regression analyses can be done with the computer language of SPSS. To enhance the learning effect, students are encouraged to preview concepts and main points. The content of this course is covered through reading, discussions, calculating statistics, writing, and working with the computer.

II. Course Objectives
1. To understand useful applications of multiple regressions.
2. To know how to conduct multiple regression analyses.
3. To learn how to report the results of multiple regressions in writing articles for publication.
4. To improve the skills in evaluating findings and conclusions of empirical studies in social research.
5. To know how to use SPSS to analyze multivariate data.

III. Books
Pedhazur, E. J. (1997). Multiple Regression in Behavioral Research. 3rd Edition. FL: Harcourt Brace College Publishers.
Agresti, A. & Finlay, B. (1997). Statistical Methods for the Social Sciences. 3rd Edition. New Jersey: Prentice-Hall.
IV. Grading systems
The final grade is composed of three parts:
1. Assignments and participation in class provide 20% of the final grade. About 4 assignments are made.
2. A midterm exam counts for 40% of the final grade.
3. A presentation of multiple regression examples from the literature accounts for 40% of the final grade. Students should read two empirical articles applying the multiple regression methods. Then you need to present the following points:
1) the study purposes
2) research questions or hypotheses
3) reasons of using the multiple regression analyses
4) implications of research findings
5) compare these two papers, and critique on them (please offer constructive commets)

V. Class Schedule and Reading
09/23：Introduction (correlation and simple regression)
09/30：Overview of multiple regressions
Pedhazur, chapter 2
10/07：Regression diagnostics: ideas
Pedhazur, chapter 3
10/14：Regression diagnostics: computer application
Class handouts
10/21：Elements of multiple regression analysis
Pedhazur, chapter 5，chapter 10, p. 319-322
10/28：Statistical control: partial and semipartial correlation
Pedhazur, chapter 7
11/04：Variance partitioning
Pedhazur, chapter 9
11/11：Computer application and data presentation
Class handouts
11/18：Midterm exam
11/25：Multicollinearity
Pedhazur, chapter 10, pp. 294-318
12/02：Categorical independent variables: Dummy, effect, and orthogonal coding
Pedhazur, chapter 11 to p. 360
12/09：Interaction effects
Pedhazur, chapter 12, pp. 425-437.
12/16：Categorical dependent variable: Logistic regression (I)
Pedhazur, chapter 17
12/23：Categorical dependent variable: Logistic regression (II）
Class handouts
12/30：Factor analysis
Class handouts
01/06：Introduction of causal models: Path analysis and structural equation modeling
Pedhazur, chapter 18 ＆19
01/13：Turn in final papers