STATISTICAL ANALYSIS IN EDUCATIONAL RESEARCH:
ANALYSIS OF VARIANCE
Education 250B
Spring 2005
MW F 11:00 - 12:30
CERAS 130—Big Tree
Instructor:
Teaching Assistant:
Richard J. Shavelson
Cubberley 308
723-4040
richs@stanford.edu
Kun Yuan
Cubberley 338
724-9085
katyuan@stanford.edu
Office Hours:
Office Hours:
10:00 - 11:00 Wednesday
Cubberley 308
or By Appointment
12:30-1:30 Wed & Fri
Cubberley 338
or By Appointment
PURPOSE OF THE COURSE
This course is intended to provide students with a working knowledge of and skills in the analysis of data
from experiments and surveys (with categorical independent variables) using the Analysis of Variance.
Students will develop knowledge of and skills in underlying statistical models, matching statistical models to
research designs, in using the computer software to conduct appropriate statistical analyses, and to interpret
and to report findings.
OVERVIEW OF THE COURSE
The first five weeks of the course cover the basic concepts and procedures used in one-way and factorial
analysis of variance (ANOVA) with between-subjects designs. Fixed, random, and mixed models ANOVA
are covered as methods for estimating strength of association between treatment and outcome, and carrying
out both planned and post-hoc comparisons. In the next three weeks, ANOVA models for within-subjects
(randomized-blocks) and mixed (split-plot) designs are presented. In week 9, regression and analysis of
variance will be integrated in the analysis of covariance. Week 10 will be used for “catch up” and for advice
on the final project to be completed by June 8 (see below).
This course will use a combination of readings, lectures, hands-on activities, computer labs and writing of
mini-research papers to impart knowledge and develop practical skills for carrying out statistical analyses and
reporting findings. Typically lectures and activities will be integrated with computer labs—data analysis,
interpretation, and reporting. Recognition, use, and interpretation of appropriate statistical models for various
research designs are crucial to understanding—the primary theme of the course.
TEXTBOOKS (On Reserve in Cubberley Library)
Required:
Ruiz-Primo, M.A., Mitchell, M., & Shavelson, R.J. (1996). Student guide for Shavelson statistical reasoning
for the behavioral sciences (3rdEd.). Boston: Allyn & Bacon. [May be out of print and unavailable—
checking]
Shavelson, R.J. (1996). Statistical reasoning for the behavioral sciences (3 rdEd.). Boston: Allyn & Bacon.
Supplemental:
Hays, W.L. (1994). Statistics (5rdEd.). NY: Harcourt Brace College Publishers.
Kirk, R.E. (1995). Experimental design: Procedures for the behavioral sciences (3rdEd.). NY: BrooksCole Publishing Company.
Winer, B.J., Brown, D.R., & Michels, K.M. (1991). Statistical principles in experimental design. NY:
McGraw-Hill.
Education 250B Syllabus
2
COURSE REQUIREMENTS
This course is graded pass-fail. To pass, you are expected to attend and participate in class, complete each
and every assignment competently; and complete the final project competently. Lecture notes, assignments,
and homework are all posted on COURSEWORK. Please check CourseWork frequently. When new material
becomes available, we’ll send you an email and announce it on CourseWork.
(1)
Class Participation
(2)
Homework Assignments
Homework assignments will be every two weeks (usually!) and due at 5PM (see below)—You can
either hand it in to Kun earlier in class or drop it off outside Rich’s office (Cubberley 308). For the
most part, you will be provided a question and data, and asked to carry out an analysis to answer the
question.
(e)
Final Project
For the final project you will be given a study description, related research literature, and a data set.
Your task is to: (a) frame the question(s) examined in the study in terms of the relevant policy
context; (b) briefly relate relevant past research (provided with the data set) to your study questions
and methods, and the policy implications therein; (c) describe the study’s design (provide a design
schematic) and data set; (d) present your analyses and for each assumption underlying your analyses,
present logical and/or empirical evidence that bears on the tenability of the assumption; (e) report
and interpret the results of your analysis; (f) draw implications of the findings for the problem
area/policy-maker audience; and (g) cite study limitations, if any.
COURSE SCHEDULE AND TOPICS
Date
Topic

March 30
- April 1
April 4 –
8
April
11 - 15

One-way ANOVA & Planned and Post-Hoc
Comparisons
Homework #1:_Effects of Drugs on Depression
(posted March 29)
Shavelson (S) Sect. V & 13, Ruiz-Primo
(R-P) 13, Hays (H) 9-11 & 13, Kirk (K)
3-6, Winer (W) 2-3



Post-Hoc Comparisons (Continued)
Factorial ANOVA
Homework #1 due: April 11 at 12:30PM
See above
See CourseWork
S 14, R-P 14, H 12, K 9 & 10, W 5 & 6




Homework #1 due at 12:30 Monday
Factorial ANOVA (Continued)
Research Design
Homework #2:_Research Design “Test”
(posted on April 13—take test on
CourseWork)
Homework #3:_Effects of Different Levels of
Text Processing on Recall (posted on April
15)
See above for Factorial ANOVA


Readings
S Ch. 1, R-P, Ch. 1, K Ch. 2, W Ch. 1
See CourseWork
Please submit all homework and final project in hardcopy only; emailed files not
accepted.
Education 250B Syllabus
3
April
18 - 22



Homework #2 due at 12:30PM Monday
Factorial ANOVA (Continued)
Homework #3 due on April 25 at 12:30PM
See above for Factorial ANOVA
S Ch. 1, R-P, Ch. 1, K Ch. 2, W Ch. 1
See CourseWork
April
25 - 29


Homework #3 due Monday at 12:30PM
Nested (Hierarchical) ANOVA
Dayton, C.M. (1970). The design of
educational experiments. New York:
McGraw-Hill, Chapter 6, pp. 198-209.
May 2 –
May 13


Randomized Blocks ANOVA
Homework #4: What’s Your Altitude? Are
You Sure? (posted May 4)
Homework #4 due on Friday, May 13 at
12:30PM
S Sect VI, Ch 15, R-P 15, H 13, K 7 &
10, W 7
Split-Plot ANOVA
Homework #5: Effect of Teaching Method on
Middle-School Mathematics Achievement
(posted May 18)
S 16, R-P 16, K 12, W 7
S 17, R-P 17, H 17, 15, W 10

Analysis of Covariance
Review of Course
Homework #5 due on Friday, June 3 at
12:30PM
Final project (posted June 1)


Fnal Project Due at 5:00pm
HAPPY SUMMER VACATION!!!
See CourseWork

May 16 –
May 27
May 30–
June 3
June 8
>5:00PM





See CourseWork