Education | Intermediate Statistics Applied to Education
Y502 | 5981 | Dr. Joanne Peng

```This is a course designed primarily for advanced graduate students
who anticipate future applications of quantitative analyses
techniques.  Topics covered in this course include a brief review of
descriptive statistics, correlational indices, comparisons of means
(t-test, one-way, and two-way analysis of variance), and regression
methods.  Prerequisite of this course is successful completion of
Y520, or P501, or equivalent.

Objectives

1.To acquire basic 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 analysis
techniques covered in this course were used.

3.To carry out numerical analyses of data by hand or by SPSS software
under Windows.

Textbooks and Websites

Kirk, R. E. (1999). Statistics-An introduction (4th ed.,), Orlando,
FL: Harcourt Brace & Company.

Hayes, W. A. II. & Hayes, C. A. (1999). Study guide to accompany
statistics-An introduction, Orlando, FL: Harcourt Brace & Company.

SPSS Inc. (latest). SPSS Base 12.0: Application Guide. Chicago, IL:
SPSS Co.

http://trochim.human.cornell.edu/kb/regrmean.htm

http://www.statsoft.com/textbook/stathome.html

Assignments, Exams, and Labs

For each topic covered in this course, practice problems and readings
taken from Kirk or other sources will be assigned. Students are
expected to be up-to-date on the readings since class time is
structured around in-depth understanding of statistical concepts and
practice. Practice problems will be graded on a 0-1-2- scale where 0
means completely wrong or did not complete on time, 1 means partially
correct, and 2 means completely correct. In addition, each student is
required to take three in-class exams.

You should have a valid student account that facilitates our
communication via e-mail and enables you to analyze data by SPSS. My
e-mail address is PENG. The AI for this course is Tsai-Feng Wang
(TSWANG) in ED 4003.

The attendance to the lab or the class is optional; but repeated
absences are known to researchers and students to affect learning.
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, assigned readings, or any
administrative aspect of the course, and (c) instruction on basic
SPSS command language and execution.  The first lab is scheduled for
this Wednesday, January 14th in Room 2015 from 4 pm to 5 pm.

Student’s performance in this course will be evaluated based on the
required exams and assignments completed.  The three in-class exams
and assignments each contribute 25% toward the overall mastery
level.  A course grade, expressed in letters, will be determined for
each student according to the following cutoffs on the overall
mastery level:

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

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 this course, you may
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.

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.

Points to Ponder

1.Nothing is easier than being busy.

2.Nothing is harder than staying focused.

3.Priorities are not what you do but who you are.

4.Good study goes in before good grade goes on.

5.The word for learning in Greek is   [manthan ]—to increase
one’s knowledge or to be increased in knowledge, frequently by
inquiry or observation.  This Greek word is akin to   which
denotes “a disciple,” a follower of the master by his/her example and
by the application of the knowledge gained from the master.
Thus, “learning” implies a process of becoming mathematical (inclined
to learn, to be alert, or to ascertain) and the act of practicing
what is learned so as to be a different person.

6.With this definition for “learning,” I therefore
interpret “teaching” to mean guiding and nurturing a learner in
becoming mathematical.

Tips for Successful Learning in Y502 (or any stats. Course)

•For each hour in the class or the lab, always plan on spending three
hours in reviewing/previewing materials.

•Establish a good study habit by following these steps:

I.Preview materials before coming to each class;

II.On Mondays and Wednesdays, come to classes prepared; and

III.Review materials immediately after each lecture or lab.

•Always bring three things to class/lab:

A.The textbook by Kirk.

B.A functional calculator comparable to Casio models fx260 Solar,
SL200, TI 25 or Sharp EL-531 lb.

C.All notes and handouts ever distributed in class; preferably
already organized in a three-ring notebook form.

email. The instructor’s role is to help you learn and understand the
material. Asking questions gives the instructor a chance to
detect “problem” areas and try to facilitate the learning process.

•If you find it helpful, work closely with one or two of your
classmates and verbalize your understanding, such as the logic behind
hypothesis testing. But don’t become overly dependent on a classmate
individual responsibility; there will be activities/situations in
which you will have to engage in alone.

•About the exams, (a) forget about cramming the night or the week
before; this habit only immobilizes you and convinces you that
you “can’t do statistics”; (b) exams are always cumulative because of
the nature of materials tested; and (c) the textbook is not meant for
casual reading, it must be read at least three or four times before
it makes sense.

Warning: Taking this course may change your intellectual life
forever!!!

Spring, 2004	C.Y. Peng
2:30 - 3:45 MW  ED 0101 	 peng@indiana.edu
4:00 - 5:00  W  ED 2015 (Lab) 	4050ED,856-8337

Schedule for Y502 (Section 5981)

Kirk

#1		Orientation to the course
Review of fundamental concepts
Chapter 1

#2		Frequency distribution/graphical representation
Chapter 2
Central tendency, and variation
Chapters 3 & 4

#3		The box plot,Percentiles, Percentile ranks,
Skewness, and Kurtosis
Chapter 4
Probability
Chapter 7

#4		Random variables and Probability Distributions
Chapter 8

#5		Normal distribution
Chapter 9

TEST #1	Wednesday in Ed. Library
Ch. 1-4, 7-8
********	**************************************************
**************

#6		Normal distribution and sampling distribution
Chapter 9

#7		Hypothesis testing and one-sample t-test
Chapter 10, 11
Point and interval estimations

#8 	Hypothesis testing and interval estimation for
comparison of two-sample means
Chapter 12

#9 	Hypothesis testing and interval estimation for
comparison of k-sample means
Chapter 14

#10	Comparison procedures of means
Chapter 14

#11,12,13	Two-way analysis of variance
Chapter 15 (not 15.2)

TEST #2	Wednesday in Ed. Library
Ch.9-10,11.1-11.2,12,14
********	**************************************************
**************

#14	one-sample Pearson’s r, Spearman rs
Chapters 5 & 11.5
and hypothesis testing of Pearson’s r

#15	Simple regression
Chapter 6.1-6.4

********	  ***************************************************
***************

Final Exam  	Time and Place to be announced later in class.
Ch. 5, 6.1-6.4,

11.5, 15 (not 15.2)

======================================================================
=============

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. They will be
communicated to each enrolled student via the electronic mail.

Spring, 2004	C. Y. Peng
2:30 – 3:45 pm      MW ED 0101	peng@indiana.edu
4:00 – 5:00 (Lab)      W ED 2015	4050 ED, 6-8337
Y502 Lecture No. and Dates (Section 9039)

Week
The week of	Monday	Wednesday	Comments

1	1/12 (M)

video: What is statistics?

2	1/19 (M)
	Class does not meet on Monday (1/19)
3	1/26 (M)		

4	2/2 (M)	
 continued

5	2/9 (M)

1st Exam 	Help session on Monday
4 to 5 pm
6	2/16 (M)		Review of 1st Exam
 started
7	2/23 (M) 	 finished


8	3/1 (M)	

9	3/8 (M)	 	

10	(Spring break, no classes)

11	3/22 (M)	

12
3/29 (M)	 	2nd Exam	Help session on
Monday
4 to 5 pm
13	4/5 (M)	 	Review of 2nd Exam
 started
14	4/12 (M)
 finished 	
15	4/19 (M)


16	4/26 (M)		Wrap up and
Course Evaluation

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