Education | Intermediate Statistics Applied to Education
Y502 | 5498 | Dr. Joanne Peng

Course Description

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.


1.To acquire basic skills necessary for applying statistical
principles of inference to well-defined behavioral and educational

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.


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 10.0: Application Guide. Chicago, IL:

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 and assignments will be graded on a random
basis. In addition, each student is required to take three in-class
exams.  The specific contents of and instructions on exams 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 SPSS software.
Thus, a limited prior knowledge of computers is assumed.  My e-mail
address is PENG; the AI assigned to this course is Stephanie
Charleston, her e-mail address is STCHARLE. Stephanie's office is
4015B and phone is 856-8313, ex.                 .

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
Wednesday, January 10th in Room 2015 from 5:30 pm to 6:30 pm.

Grading System

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

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 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.

Points to Ponder

Nothing is easier than being busy.

Nothing is harder than staying focused.

Priorities are not what you do but who you are.

Good study goes in before good grade goes on.

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.

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:

Preview materials before coming to each class;
On Mondays and Wednesdays, come to classes prepared; and
Review materials immediately after each lecture or lab.

Always bring three things to class/lab:

The textbook by Kirk.
A functional calculator comparable to Casio models fx260 Solar, SL200,
TI 25 or Sharp EL-531 lb.
All notes and handouts ever distributed in class; preferably already
organized in a three-ring notebook form.

Don't be shy about asking questions, either directly or through 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
or friend to answer your questions. Ultimately, learning is an
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

Week       Topics       Readings in Kirk

#1 Orientation to the course
Review of fundamental conceptsChapter 1

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

#3 The box plot,Percentiles, Percentile ranks,
Skewness, and KurtosisChapter 4
ProbabilityChapter 7

#4 Random variables and Probability DistributionsChapter 8

#5 Normal distribution Chapter 9

TEST #1 February 7th (W) Place to be announced.  Ch. 1-4, 7-8

#6 Normal distribution and sampling distributionChapter 9

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

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

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

#10 Spring break, no classes

#11 Comparison procedures of meansChapter 14

TEST #2 March 28th (W) Place to be announced.Ch.9-10,11.1-11.2,12,14

#12,13,14 Two-way analysis of varianceChapter 15 (not 15.2)

#15 one-sample Pearson's r, Spearman rsChapters 5 & 11.5
and hypothesis testing of Pearson's r

#16 Simple regression Chapter 6.1-6.4

Final Exam  Monday (4/30) from 5-8 pm, 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.

The week of Monday Wednesday Comments

1 1/8 (M)

video: What is statistics?

2 1/15 (M)
No class on Monday (1/15)
3 1/22 (M)

4 1/29 (M)
Wed. Lab will be used for
the review before 1st Exam.

5 2/5 (M)
1st Exam

6 2/12 (M)Review of 1st Exam

7 2/19 (M)

8 2/26 (M)

9 3/5 (M)

(Spring break, no classes)

11 3/19 (M)
Wed. Lab will be used for
the review before 2nd Exam.
12 3/26 (M)
2nd Exam
13 4/2 (M)Review of 2nd Exam

14 4/9 (M)

15 4/16 (M)

16 4/23 (M)Wrap up and
Course Evaluation
Wed. Lab will be used for
the review before the Final Exam.