Education | Statistical Design of Educational Research
Y603 | 5504 | 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
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 on exams and the critiques 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
the e-mail utility and enable you to analyze data by using 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
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.
Lecture/Topics/Readings in Kirk
Orientation to the course (Unit 0)
Research strategies, controlling nuisance variables Chapter 1
Experimental designs: An overview Chapter 2
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 5.1,5.2
An example of one-way ANOVA 5.3
Assumptions in ANOVA 3.5, 3.3 (fixed)
Post-hoc (A Posteriori) comparisons of means4.5(Tukey),4.6(Scheffe)
squared 5.4, 5.5
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 9.1, 9.2
Example of a 2-way ANOVA 9.3, 9.4
Interpretation of interactions 9.3, 9.6
squared, Effect size, power, and
sample size determination 9.8, 5.6
(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 7.1,7.2,7.4
Generalized randomized block (GRB) design 7.9, 7.10
Introduction to Latin-square designs 8.1,8.2,8.3
An example of LS-p design 8.5
Latin-squares with replications 14.9
(Spring Break and the first article critique assigned)
Date/Topics/Readings in Kirk
Introduction to & an example of hierarchical design 11.1-11.5
Advantage and disadvantage of hierarchical designs 11.9
Introduction to split-plot factorial (SPF) designs 12.1
An example of SPFp.q design 12.2, 12.3
Assumptions underlying the SPF designs 12.4
Introduction to the SPFpr.q design 12.8
(The second article critique assigned)
Introduction to the SPFp.qr design 12.10
Introduction to and rationale for ANCOVA 15.1-15.2
an example of one-way ANCOVA 15.1-15.3
Assumptions underlying ANCOVA designs 15.4
Continued with one-way ANCOVA 15.1-15.4
Two-way ANCOVA 15.9
Course evaluation and wrap-up
(The second take-home examination, Section 5.8, Chapters 7-9, 11,12,
and 15 in Kirk)
May 1st (M) 5 pm the second take-home examination is due in Room 4050
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
Y603 Lecture No. and Dates
The week of Monday/Wednesday Comments
1 1/8 (M) 1 / 2 3 during the lab
2 1/15 (M) / 4 No class on Monday
3 1/22 (M) 5 / 6
4 1/29 (M) 7 / 8
5 2/5 (M) 9 / 10
6 2/12 (M) 11 / 12
7 2/19 (M) 13 / 14
8 2/26 (M) 15 / 16
9 3/5 (M) 17 / 18
10 (Spring break, no classes)
11 3/19 (M) 19 / 20
12 3/26 (M) 21 / 22
13 4/2 (M) 23 / 24
14 4/9 (M) 25 / 26
15 4/16 (M) 27 / 28
16 4/23 (M) 29 / Course Evaluation