1
EDF 7405
Advanced Quantitative Foundations of Educational Research2011 Fall Term
Instructor:

James Algina

Office:119D Norman Hall

Phone:

273-4305

Email:

algina@ufl.edu

Course Web Page: http://plaza.ufl.edu/algina/index.html
To help me keep track of email messages, please include EDF 7405 and your last name inthe subject line of any correspondence sent via email.

I have created a distribution list using your GATROLINK email address. If you do not
use your GATROLINK account regularly, please make sure your GATROLINK accountforwards to the account you do use regularly.

Office Hours: Tuesday 5:15-6:15 PM, Thursday 4:15-6:15 PM, and by appointment. (To set anappointment, send me an email indicating several times when you are free.)Course Description
An introduction to the use of correlation and regression in educational research and moregenerally in behavioral science research.
Prerequisite
The prerequisite for this course is a statistics course including the following topics:
measures of central tendency and variability, correlation, hypothesis testing (null and alternate
hypothesis, Type I error rate, and power), t-tests on means, and one-factor analysis of variance.
If you have not taken a class that covered these topics, please talk with me today about
whether you should drop EDF 7405.
Texts
Sections of the following texts are read in this courseYounger, M. S. (1979). A handbook for linear regression. North Scituate, MA:
Duxbury Press, 1979.
Agresti, A., & Finlay, B. F. (2009). Statistical methods for the social sciences (4th ed.).
San Francisco: Dellen Publishing Co.

2The sections of the Younger text are available at Target Copy. The Younger text andthe Agresti and Finlay text are on reserve at the Education Library. The Agresti and Finlay text
can be purchased at the HUB and at other bookstores in town.
Other Materials
There is a packet of handouts at Target Copy Center (1412 West University Avenue).
Computer Manuals
In this course the Statistical Analysis System (SAS) is used for computerized dataanalysis. You are not required to buy any computer manuals. However, some students may findsuch manuals helpful. An introduction to SAS is provided byDelwiche, L. D., & Slaughter, S. J. (2003). The little SAS book, a primer (3rd. Ed.).
Cary, NC: SAS Institute, Inc.
A presentation of regression using SAS is provided byFreund, R. J., & Littell, R. C. (2000). SAS System for Regression (3rd. Ed.). Cary, NC:
SAS Institute, Inc.
Information about licensing SAS is available on the course website. See SAS Student
Use Program. Students can also access SAS in 115 Norman Hall. This lab is usually open
between 9:00 and 5:00 but the hours can be irregular on Fridays. The computers with SAS
installed on them are also used by students who are not enrolled in EDF 7405.
Some of you have used SPSS for Windows in EDF 6402 or EDF6403. You can use
SPSS to do the computer problems in the course. I have prepared materials that show how to use
SPSS for Windows to do the analyses presented in class. These materials also include SPSS
printouts for the analyses presented in class. (Please note that I could not get SPSS for Windows
to do all possible subsets regression.) These materials are available on the course web page.
Please note that you are not likely to be able to use these materials effectively if you are notan accomplished user of SPSS. Even if you use SPSS to do the computer problems, you must
know where to find information on SAS printouts.
Course Requirements
Examinations. The course is divided into three sections. An examination follows eachsection. Examination dates are shown on the list of course topics and are approximate.
Descriptions of the content of the exams are provided in the material available at Target Copy.
Exercises. The materials available at Target Copy contain exercises for the class. For
each section of the course, asterisks mark several exercises. The marked exercises for asection of the course must be submitted for a grade. Due dates will be announced in class.
You will have between two and seven days to complete each exercise.

3Calculator. For exams, it will be helpful to have a calculator that does addition,subtraction, multiplication, division, and square roots. You may not use your phone as acalculator.
Handheld Electronic Translators. These devices can be used only if they are not capableof storing information that is input by the user. If you plan to use a Handheld ElectronicTranslator, you will have to show it to me at least three weeks before an exam and may have toleave it with me.
GradesEach examination will be scored on a percentage correct scale (0-100%). Each exercise
will be scored on a 13-point scale. The relationship between scores and grades is shown in thefollowing table
Exams
Exercises
Score
Grade Score Grade12A+
 90
A11A
A10
A86 2  90
3

B+
9B+
83 1  86 233
B
8B80  83 13

B7
B 76 2  80
3

C+
6C+
 73 1  76 233
C
5C 70  73 13
C4C 66 2  70
3

D+
3D+
 63 1  66 233
D2D
 60  63 13

D1
D56 2  50
3
E0E
 56 23



A late exercise will receive a maximum score of 8.

4For each of the three sections of the course, averaging scores on the individual exercises
into a single score will compute an exercise score. Exercise scores are averaged over sections
and examination scores are averaged over sections. The following table is used to determine
grades:ExamD
DD+
C
CC+B
B
B+A
ADD
DD+C
CC+B
B
B+AA

D
D
D
D+C
C
C+B
B
B+A
A

D+D+
D+
D+C
C
C+B
B
B+A
A

C
CCCC
CC+B
B
B+A
A

CC
C
C
C
C
C+B
B
B+A
A

Exercise
C+B
C+B
C+B
C+B
C+B
C+B
C+B
B
B
B
B
B+
B+A
A
A
A

B
B
B
B
B
B
B
B
B
B+A
A

B+B
B
B
B
B
B
B
B
B+A
A

A
B
B
B
B
B
B
B
B+B+A
A

A
B
B
B
B
B
B
B
B+A
AAA+
BB
B
B
B
B
B
B+
AA
A

Students should do the exercises not only to help understanding, but also because doing so canimprove your grade. An important feature of the grading system is that exercises cannot hurt
your grade. For example if your exam average is 831/3 (a B+) and your exercise score is 8 (a B),
your grade would be a B+.
Studying for the Course
The following are suggestions about studying for the course. Following these shouldhelp most students, but in particular will help students who have difficulty in quantitativecourses.
1. Read the text before a topic is covered in class. This will provide backgroundinformation to help you comprehend the lectures.
2. Study your notes after the class.
3. Do the exercises that are not submitted for a grade as soon as the material testedby the exercises has been covered in class. The answers are in the Target materials.
4. Ask questions about the material and exercises that you do not understand. The course
moves quickly and neglected misunderstandings may never be resolved and may make futurematerial difficult to understand. Ask questions in the class and/or consult with the instructor
outside of class.

5Academic Honesty
Students are expected to do their own work on exercises that are submitted for a grade.
You should not solicit help with your exercises from other people (including students andfaculty), nor should you provide help to other students. Soliciting help includes discussing
with other people (including students and faculty) what the appropriate approach to an
exercise might be.
If you need to discuss an exercise you should talk with me. Be advised however that if
your question is about the correct analysis for an exercise I will usually require you to phrase
your question about analysis in general and not about the specific exercise. If you know thecorrect analysis and have a question about a computer program or formula to implement theanalysis, I will usually answer the question directly.
You are expected not to cheat on examinations.
In the event a violation of standards of academic honesty occurs, I will contact the Officeof Student Conduct and Conflict Resolution to determine if it is the first violation. If not I willturn the matter over to the Student Conduct and Conflict Resolution. For a first offense theexercise or the exam will receive a grade of zero.
Students with Disabilities
Students with disabilities who need reasonable modifications to complete assignments
successfully and otherwise satisfy course criteria are encouraged to meet with the instructor as
early in the course as possible to identify and plan specific accommodations. Students must
supply a letter from the UF Office for Students with Disabilities to assist in planning
modifications.

6

Tentative
DateFirst Section
TopicReading*

I. Simple Linear Correlation and Regression
8/23-8/25

A. Summarizing Data on Two Variables. Correlation.
Review of SAS

Younger
Section 8.3

8/25-8/30

B. Review of Statistical Inference: Inference on theCorrelation Coefficient.

Younger:
Section 8.4

8/30-9/01

C. Simple Linear Regression Model.

Younger:
Chapter 1

Least Squares Estimation.

Uses and Interpretation of the Regression
Equation.
9/01-9/06

D. Measuring Error in Estimation

9/06-9/8

E. Inference in Simple Linear Regression.

9/8-9/13

F. Checking Violations of Assumptions

9/15-9/20

G. Comparing Correlation Coefficients and Comparing
Slopes

9/22

WRAP UP AND REVIEW

9/27

EXAM 1Younger:
Chapter 2(pp. 21-31 adn4045)
Younger:
Chapter 5Younger:
Chapter 6(skip 6.5, 6.6, and6.9)
Younger:
Chapter 6(skip 7.5 and 7.7)
Younger:
Chapter 9(pp. 250-255)* Readings in Younger are listed; the material is also covered in Agresti and Finlay (Chapter 9).

7

Tentative
Date

Second Section
TopicReading

II. Multiple Regression
9/29-10/04 A. The General Multiple Regression Model. Focus on theModel for Two Quantitative Independent Variables.
Conditional Variance and Standard Error of Estimate.
Multiple, Partial, and Semipartial Correlations.
Standardized Regression Coefficients.

Agresti & Finlay
Section 10.1-10.2,
11.1- 11.3, and 11.7
(Up to Higher
Order PartialCorrelations)
Section 11.8

10/0410/06

B. Inference and Confidence Intervals.

Agresti & Finlay
Section 11.4, 11.7
(p. 350)

10/11

C. Models for a Nonlinear Relationship with a Single
Independent Variable.

Agresti & Finlay
Section 14.5

10/1310/18

D. Checking Violations of Assumptions. Models forInteraction and Quadratic Relationships.

Agresti & Finlay
Section 11.5, 14.2,
14.3

10/20

E. Multiple Regression With More Than Two
Independent. Variables. Generalization of the Model,Significance Tests and Associated Correlation
Coefficients.

Agresti & Finlay
Chapter 11(Skip 11.5)

10/25

WRAP UP AND REVIEW

10/27

EXAM 28Tentative
Date

Third Section
TopicReading

II. Multiple Regression (continued)
11/0111/03

F. Strategies in Hypothesis Testing. Testing the Addition ofSeveral Variables to a Model. Multiple Partial Correlation.
Multiple Semi-Partial Correlation

Agresti & Finlay
Section 11.6

III. Models with Categorical Independent Variables
11/0811/15

A. Models with One Categorical Independent Variable11/1711/22

B. Multiple Regression with One Quantitative Variable andOne Categorical Variable.
C. ANCOVA in Experiments with Simple Random
Assignment.
D. ANCOVA in Treatment Comparisons Based on Nonrandom
Experiments.

11/29

IV. Selecting Predictors.

12/1-12/06

V. Regression for Categorical, Ordinal, and Count
Dependent Variables

12/9

REVIEW (TIME AND ROOM TO BE ANNOUNCED)

12/12

EXAM 3 2:45-5:15

Agresti & Finlay
Section 12.112.2 (review),
12.3
Agresti & Finlay
Chapter 13

Agresti & Finlay
Section 14.1
Agresti & Finlay
Section 14.4,
Section 15.115.5