Stephen G. Sireci, Ph.D.

156 Hills South


Office Hours for Fall, 1999

Thursday: 12:30-3:30 p.m.

Other times by appointment

Syllabus for Fall, 1999

Course Objective: To provide the knowledge necessary for understanding and critiquing educational research, and the skills necessary for conducting statistical analyses on educational data. Successful completion of this course will enable students to formulate designs for collecting data and analyze data of different measurement levels using statistical models such as one-way analysis of variance (ANOVA), factorial ANOVA, repeated measures ANOVA, and multiple regression. In addition, related univariate and multivariate procedures will be discussed. Students will also gain proficiency in using the SPSS statistical software package to perform data analyses.

Course Requirements:

1. Attendance and Participation: Students are expected to actively participate in class. Students taking this course for credit will need to attend all (or nearly all) classes. Statistics is like a language, and so if you miss more than one class, it is likely that you will not be able to keep up with the material, Therefore, if you anticipate missing more than one class, or if you are unable to make it to class on time, you should consider taking the class another semester when you are able to attend all sessions. Anticipated absences should be brought to the attention of the professor in advance.

2. Assignments: Homework assignments will be given throughout the semester. These assignments may include textbook or class exercises, group projects, readings, and computer exercises.

3. Examinations: There will be two take-home examinations, one due around the middle of the semester, and one due at the end of the semester. These examinations include analysis of one or more data sets using the statistical models presented in class. Successful completion of these examinations will require mastery of the material presented in class.

Grading: Your final grade in this course will be determined by your performance on the assignments, examinations, and your attendance/participation. The percentages of your final grade for each of these areas are:

Activity % of Grade

Attendance/Participation 5

Assignments 35

Midterm Exam 30

Final Exam 30

Total 100%

Make-up policy: Late assignments will be reduced by one-letter grade for each day late (e.g., a maximum grade of a "C" will be given to a perfect exam submitted two days late). Unforseen emergencies, as determined by the professor, will be exceptions to this policy.

Primary Textbook:

Howell, D.C. (1997). Statistical Methods for Psychology (4th edition). Belmont, CA: Wadsworth. [This book is available in the textbook annex. The 3rd edition of this book is also acceptable. This book is comprehensive and covers all the material we will discuss in class (and then some). However, people learn statistics in different ways, and so I encourage you to look at other textbooks.]

I realize some students will have other textbooks from Intro Stat I. Howell's (1999) book, Fundamental Statistics for the Behavioral Sciences (4th edition), is also acceptable, although it is written at a substantially lower level, with less detail than the primary text listed above. Other books I recommend for helping understand course material are:

1) Cohen, J. & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd edition). Hillsdale, NJ: Lawrence Erlbaum. This is a classic text on multiple regression that does a particularly thorough job explaining dummy variable coding in regression analysis

2) Keppel, G. (1982). Design and analysis: A researcher's handbook (2nd edition). Englewood Cliffs, NJ: Prentice Hall. This text provides comprehensive coverage of ANOVA designs and models.

3) Kerlinger, F. N. (1986). Foundations of behavioral research (3rd edition). New York: Holt, Rinehart, and Winston. This text includes some philosophy of measurement as well as comprehensive treatment of advanced statistical topics such as ANOVA. It is a terrific book, and is partly responsible for my interest in quantitative psychology. Unfortunately, it is out of print, which makes it very hard to find.

  1. Kirk, R. E. (1995). Experimental design: Procedures for the behavioral sciences. Pacific Grove, CA: Brookes/Cole. A very good book for understanding interaction effects in ANOVA.

5) Yaremko, R .M., Harari, H., Harrison, R. C., & Lynn, E. (1982). Reference Handbook of Research and Statistical Methods in Psychology. New York: Harper & Row. A comprehensive reference handbook.

I also recommend the following journal articles:

6) Frick, R. W. (1996). The appropriate use of null hypothesis testing. Psychological Methods, 1, 379-390. [Required reading.]

  1. Huberty, C. J., & Morris, J. D. (1989). Multivariate analysis versus multiple univariate analysis. Psychological Bulletin, 105, 302-308.

8) Humphreys, L. G. (1978). Doing research the hard way: Substituting analysis of variance for a problem in correlational analysis. Journal of Educational Psychology, 70, 873-876.

I will also distribute several handouts and articles throughout the semester. DO NOT UNDERESTIMATE THE UTILITY OF THESE HANDOUTS! They are designed to make the material presented in class and in the text more understandable.

You have at least four resources for helping understand the material presented in this course. Specifically,

(a) Me: I will do my best to present material clearly in class. Your class notes will be important to you for completing assignments and examinations. In addition, I am available outside of class during my office hours and by appointment. You can also ask me questions using e-mail. See the top of the syllabus for office hours and e-mail address.

(b) The textbook: I selected this textbook because I think it does a good job of explaining the material and includes many excellent exercises. In addition, I encourage you to visit the author's web site (

(c) The handouts: These handouts are created to summarize and supplement the lectures. I strongly suggest that you review them in completing assignments and exams.

(d) Each other: Like foreign languages, it is helpful to learn statistics through discussion. I encourage you to form study groups and help each other learn this material. However, any work you turn in must be your own (see plagiarism policy below).

Plagiarism policy: All of the work you hand in must be your own. It is fine to discuss the assignments with one another. It is also fine to work together in completing assignments. Direct copying of someone else's work is not allowed. Printing out someone else's computer output, and handing it in as your own work, is also not allowed. Passing off someone else's work as your own will result in failing this course. Please see me if you have trouble completing any assignments.







Sampling Distributions Revisited


H97: 1-6

H99: 1-8, 19


Testing Hypotheses Involving Two Sample Means

Entering Data in SPSS

H97: 7

H99: 12-14


One-way Analysis of Variance (ANOVA)

H97: 11

H99: 16


One-way Analysis of Variance (continued)



Multiple Comparisons

H97: 12

H99: 16


NO CLASS: It's Monday at UMASS



Factorial ANOVA

H97: 13

H99: 17


Factorial ANOVA (continued)



Repeated Measures Designs

H97: 14 (450-485)

H99: 18


Midterm due

Correlation and Regression Revisited

H97: 9

H99: 9-10


Multiple Regression Analysis

H97: 15(509-547)

H99: 11


Multiple Regression (continued)

Partial Correlation, Dummy Variable Coding



Analysis of Covariance



Summing Up: The General Linear Model

H97: 16


Take-Home Final Due


1. Readings refer to chapters in texts. H97= Howell (1997), H99=Howell (1999)