Education | Statistical Design of Educational Research
Y603 | 5548 | Dr. Joanne Peng
1. To acquire skills necessary for applying statistical principles of
inference to well-defined behavioral and educational problems.
2. To be able to objectively evaluate manuscripts in which
(univariate) analysis of variance techniques were used.
3. To carry out numerical analyses of data by hand or by SAS software
under the Windows.
4. Can understand selected articles which address unresolved
theoretical issues in univariate statistics. These issues largely deal
with statistical assumptions or adequacy of applying certain models to
Kirk, R.E. (1994). Experimental Design--Procedures for the Behavioral
Sciences (3rd ed.,), Belmont, CA: Brooks/Cole Publishing Company.
Huck, S. (2000). Reading Statistics and Research (3rd ed.), New York,
NY: Addison Wesley Longman.
Peng, C. Y. (2000). Statistical Design of Educational Research-Course
Packet for Y603, Bloomington, IN: Indiana. University.
Peng, C. Y. (2000). SAS 1-2-3. Bloomington, IN: Indiana University.
Review or Reference Books/Website
Kirk, R. E. (1999). Statistics-An Introduction (4th ed.,), Orlando,
FL: Harcourt Brace & Company.
Hays, W.L. (1988). Statistics for the Social Sciences (4th ed.,), New
York, NY: Holt, Rinehart and Winston, Inc.
Maxwell, S.E., & Delaney, H.D. (1990), Design Experiments and
Analyzing Data: A model comparison perspective, Belmont, CA: Wadsworth
Winer, B.J. (1971). Statistical Principles in Experimental Design
(2nd ed.,), New York, NY: McGraw Hill.
Assignments, Exams and Labs
For each topic covered in this course, practice problems and readings
taken from Kirk will be assigned. Practice problems are not graded
because answers will be provided for you. You will be required
instead to complete two take-home exams and two research article
critiques. The specific instruction the required work will be
announced later in class.
You should have a valid student account on the university computing
system. This account will facilitate our communication via e-mail and
enable you to analyze data by the SAS software. Thus, a limited prior
knowledge of computers is assumed. My e-mail address is PENG, the
GA's e-mail address is WLIM (Woong Lim).
The attendance of any lab session is optional; but you alone are
responsible for the consequences of missing the labs. Activities that
typically take place in the labs include, but are not limited to, (a)
clarification of previous lectures, (b) answering questions related to
practice problems, the article critique, or any administrative aspect
of the course, and (c) instruction on basic SAS command language and
Student's performance in this course will be evaluated based on the
required two exams and two article critiques. The article critiques
count 20% (or 10% each) toward the final grade. Both take-home exams
are graded on the point system and count 80% (or 40% each) toward the
final grade. A final course grade, expressed in letters, will be
determined for each student according to the following mastery levels:
85% mastery or above -- A
80% to 84% -- A-
75% to 79% -- B +
70% to 74% -- B
65% to 69% -- B-
60% to 64% -- C +
55% to 59% -- C
50% to 54% -- C-
The letter grades should be interpreted according to the School of
Education grading policy as follows:
A Outstanding achievement.
A- Excellent achievement.
B+ Very good achievement.
B Good achievement
B- Fair achievement.
C+ Not wholly satisfactory achievement.
C Marginal achievement.
C- unsatisfactory achievement.
Incomplete will be given only for a legitimate reason as outlined in
the university's Academic Guide, and only after a conference between
the instructor and the student. Throughout the course of this
section, you may contest every grade awarded to your article critique,
exams or the overall course performance within 48 hours of receiving
such a grade. Once this "statute of limitation" has passed, it is
assumed that you willingly accept the grade(s) assigned without
Academic Honesty and Intellectual Integrity
According to P.72 of the Academic Handbook (June 1992 edition), each
faculty member has "a responsibility to foster the intellectual
honesty as well as the intellectual development of his/her students."
In order to achieve these goals, each student enrolled in this course
is prohibited from engaging in any form of "cheating" or "plagiarism."
Cheating is defined as "dishonesty of any kind with respect to
examination, course assignments, alteration of records, or illegal
possession of examinations" (p. 72 of the Academic Handbook). "It is
the responsibility of the student not only to abstain from cheating
but, in addition, to avoid the appearance of cheating and to guard
against making it possible for others to cheat. Any student who helps
another student to cheat is as guilty of cheating as the student he or
she assists. The student also should do everything possible to induce
respect for the examining process and for honesty in the performance
of assigned tasks in or out of class." (p. 72 of Academic Handbook).
Plagiarism is defined as "offering the work of someone else as one's
own" (p. 72 of Academic Handbook). "The language or ideas thus taken
from another may range from isolated formulas, sentences, or
paragraphs to entire articles copied from books, periodicals,
speeches, or the writings of other students. The offering of
materials assembled or collected by others in the form of projects or
collections without acknowledgment also is considered plagiarism. Any
student who fails to give credit for ideas or materials taken from
another source is guilty of plagiarism." (p.72 of Academic Handbook).
Evidence of student academic misconduct will result in (a) a lowered
course grade, (b) transfer out of this course, (c) dismissal from
student's academic unit, or (d) other disciplinary actions in
accordance with the guidelines outlined on p.73 of Academic Handbook.
Orientation to the course (Unit 0)
Research strategies, controlling nuisance variables
Experimental designs: An overview
Chi-square distribution 3.1
F-distribution and F statistic 3.1, 3.4
Please review the following topics on your own.
Introduction to one-way ANOVA
An example of one-way ANOVA
Assumptions in ANOVA
3.5, 3.3 (fixed)
Post-hoc (A Posteriori) comparisons of means
Orthogonal planned comparisons 4.1, 4.2
Dunn's, Dunn-Sidak procedures 4.4
Holm's and Dunnett's procedures 4.3, 4.4
Fisher-Hayter procedure 4.5
Newman-Keuls procedure 4.7
Comparison of comparison procedures 4.8
Introduction to 2-way ANOVA
Example of a 2-way ANOVA
Interpretation of interactions 9.3, 9.6
? squared, Effect size, power, and sample size determination
(The first take-home examination, Chapters 1-5, and 9 in Kirk)
CR-p design: Random-effect model approach 5.8
CRF-pq design: Random-effect model approach 9.4, 9.10
Pooling strategies used in random-effect models 9.11
Rules for deriving expected values of mean squares 9.9
Introduction to randomized block (RB) design
Generalized randomized block (GRB) design 7.9, 7.10
Introduction to Latin-square designs
An example of LS-p design
Latin-squares with replications 14.9
(Spring Break and the first article critique assigned)
Readings in Kirk
Introduction to & an example of hierarchical design
Advantage and disadvantage of hierarchical designs
Introduction to split-plot factorial (SPF) designs
An example of SPFp.q design
Assumptions underlying the SPF designs
Introduction to the SPFpr.q design
(The second article critique assigned)
Introduction to the SPFp.qr design
Introduction to and rationale for ANCOVA
an example of one-way ANCOVA
Assumptions underlying ANCOVA designs
Continued with one-way ANCOVA
Course evaluation and wrap-up
(The second take-home examination, Section 5.8, Chapters 7-9, 11,12,
and 15 in Kirk)
April 29th (M) 5 pm the second take-home examination is due in Room
Note: This is a tentative course schedule which is subject to change
without prior notice. Changes to the syllabus depend on the pace of
classroom instruction and students' learning. Any change in the
syllabus will be communicated to each enrolled student via the