Education | Statistical Design of Educational Research
Y603 | 5287 | Peng


Joanne Peng, Room 4050 Education
856-8337 or PENG@INDIANA.EDU

Objectives

	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 real-world
data.

Textbooks

	Kirk, R.E. (1994). Experimental Design--Procedures for the
Behavioral Sciences (3rd ed.,), Belmont, CA:  Brooks/Cole Publishing
Company.

	Huck/Cormier (1996).  Reading Statistics and Research (2nd ed.), New
York, NY: Harper Collins Publishers.

	SAS Institute (1990). SAS Language: Reference, Version 6 (first
ed.), Cary, NC: SAS Inc.

	SAS Institute (1989). SAS/Stat-Vol. I and Vol. II, Version 6 (4th
ed.), Cary, NC: SAS Inc.

	Hinkle, D.E., Wiersma, W. &  Jurs, S. G. (1997). Applied Statistics
for the Bheavioral Sciences (4th ed.,), Boston, MA:  Houghton Mifflin.

	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
Publishing Company.

	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 MIOMORI (Mika Omori).

	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 execution.

Grading System

	Student's performance in this course will be evaluated based on the
required exams and the 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.			B-
Fair achievement.
	A-	Excellent achievement.			C+	Not wholly
satisfactory achievement.
	B+	Very good achievement.			C	Marginal
achievement.
	B		Good 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 further dispute.

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.
Spring, 1999	
2:30 - 5:15 pm   M ED 1210	
5:00 - 7:00(Lab) W ED 2015			
Schedule for Y603 (Section 5287)

Lecture	Topics
Readings in Kirk
1		Orientation to the course  (Unit 0)
	Research strategies, controling nuisance variables
Chapter 1

2		Experimental designs: An overview
Chapter 2

3		Chi-square distribution
3.1

4		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)

5		Post-hoc (A Posteriori) comparisons of means
4.5(Tukey),4.6(Scheffe)
		T squared
5.4, 5.5

6		Orthogonal planned comparisons
4.1, 4.2
		
7		Dunn's, Dunn-Sidak procedures
4.4

8		Holm's and Dunnett's procedures
4.3, 4.4
	
9		Fisher-Hayter procedure
4.5
		Newman-Keuls procedure
4.7
		Comparison of comparison procedures
4.8

10		Introduction to 2-way ANOVA
9.1, 9.2
		Example of a 2-way ANOVA
9.3, 9.4

11		Interpretation of interactions
9.3, 9.6

12		T squared, Effect size, power, and
		sample size determination
9.8, 5.6

(The first take-home examination, Chapters 1-5, and 9 in Kirk)

13	 	CR-pdesign: Random-effect model approach
5.8
		CRF-pq design: Random-effect model approach
9.4, 9.10
14		Pooling strategies used in random-effect models
9.11
		Rules for deriving expected values of mean squares
9.9

15		Introduction to randomized block (RB) design
7.1,7.2,7.4

16		Generalized randomized block (GRB) design
7.9, 7.10

17		Introduction to Latin-square designs
8.1,8.2,8.3

18		An example of LS-p design
8.5

19		Latin-squares with replications
14.9

20		Introduction to & an example of hierarchical design
11.1-11.5

(Spring Break and the first article critique)

21		Advantage and disadvantage of hierarchical designs
11.9

22		Introduction to split-plot factorial (SPF) designs
12.1

23		An example of SPFp.q design
12.2, 12.3

24		Assumptions underlying the SPF designs
12.4

(The second article critique)

25		Computational procedure for the SPFpq.r design
12.8

26		Computational procedure for the SPFp.qr design
12.10

27		Introduction to and rationale for ANCOVA
15.1, 15.2
		an example of one-way ANCOVA
15.1-15.3

28		Assumptions underlying ANCOVA designs
15.4

29		Two-way ANCOVA
15.9

30		Advanced topics
		Course evaluation and wrap-up

(The second take-home examination, Section 5.8, Chapters 7-9, 11,12, and 15
in Kirk)

The first Monday of the exam week is the due day for the second take-home
exam.  Turn in the exam papers to  ED 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 electronic mail.