Intermediate Educational Statistics

EPSY 5381

INTERMEDIATE EDUCATIONAL STATISTICS

Credit: 3 hours

Semester: Fall 2004

Instructor: Arturo Olivárez, Jr., Ph.D.

Office #: Education 374 West Wing

Office hrs: 1:00- 4:3 p.m. Tuesday and Thursday

Telephone: (806) 742-1997 x 293

Meeting time: MW 4:30-5:50 p.m.

Room Number: Education 317 West Wing

E-mail:

Course Description

Prerequisite: EPSY 5380 and EPSY 5379.

The present course has several goals which are intended to help students understand fundamental concepts and methods of statistics as applied to educational and psychological problems. These include: Application of statistical procedures in research designs, basic and intermediate concepts for testing statistical hypotheses, construction and interpretation of confidence intervals, and applying selected nonparametric techniques.

Instructional Units

1. An introduction to the different aspects involved in applying statistical concepts to the solution of educational and psychological research questions. These will include the differentiation of populations and samples, descriptive versus inferential statistics, parametric versus nonparametric procedures, and experimental versus statistical research control.

2.An introduction to the different statistical procedures required for solution of questions derived from one-sample, two-sample (dependent and independent), and k-sample. This includes the selection of the appropriate test of significance and estimation for solving each of the research design questions.

3.An introduction and implementation of the different types of sampling techniques commonly used in educational research with great emphasis given to random samples and the importance of replication.

4.Introduction and application to different statistical concepts, procedures, and problems for testing hypotheses and constructing confidence intervals. The steps involved in significant testing and confidence interval estimation will also be emphasized and applied.

5.Introduction and differentiation between quantitative and qualitative variables, including the four levels of measurement.

1. Introduction to analysis of variance, multiple comparison techniques, linear regression, multiple regression, correlation, multiple correlation, analysis of covariance, and chi-square tests for independence and association. These concepts will be the major focus of the course and the student will complete every problem assigned form each of the above procedures.

Textbooks and Other Required Reading, Other Instructional Resources

Hinkle, D. E., Wiersma, W., & Jurs, S. G.(2003). Applied Statistics for the Behavioral Sciences. 5th ed. Houghton Mifflin, Boston.

The instructor may also require, on occasion, additional reading from other sources. This may be assigned during the semester. Additionally, presentation of SAS and/or SPSS examples will be provided for the student as demonstration of how computer statistical packages may be used to facilitate the computation of statistical problems.

Course Evaluation

1. Comprehensive exams. The student will earn a satisfactory grade on 4 exams. The format of the test will include multiple choice questions, computational problems, and conceptual questions. These exams will be in-class emphasizing concepts and computational applications. Each of the unit exams will count approximately 100 points. These exams will yield a total of 80% of your final grade. The length of time for these exams is only the duration of one regular class period.

1. Chapter exercises. The student will be assigned problems exercises from each chapter, including computer problems, for credit. The chapter exercises will be assigned after each chapter presentation (See tentative schedule) and are to be turn-in in a timely manner. These problems are worth a total of 100 points. Your efforts on this task will yield a total of 20% of your final grade.These percentage points are not guarantee unless you turn in all problems assigned on each chapter in a timely manner. The number of problems assigned is based on the ability from each student in staying current with the presentation of the chapter material. Students are still encouraged to do as many problems as needed for complete understanding of the statistical concepts at hand.

Grading summary of course assignments.

4 Chapter exams 400 points 80%

10 Chapter exercises 200 points 20%

Total 600 points 100%

Letter grade assignment (University guidelines)

90.0--93.9A-94.0--96.9A97.0-99.9A+

80.0--83.9B-84.0--86.9B87.0-99.9B+

70.0--73.9C-74.0--76.9C77.0-99.9C+

60.0--63.9D-64.0--66.9D67.0-99.9D+

< 60F

In order to obtain a grade based on the criteria above, all assignments must be completed before the session is over. If a student fails to complete the assigned tasks, then an incomplete grade, an I, will be posted in the student record. Students are discouraged to place themselves in that position since the grading system changes once the student does not finish the required material for the semester. The changes on grading procedures are left to the discretion of the instructor. Additionally, some rules to follow while enrolled in this course:

1)Please be Courteous To Your Classmates and Instructor. See “civility in the class room below”

2)I Reserve The Right to Change Procedures, Readings, And Topics As Necessary, With Ample Warning.

3)If you must miss more than five class meetings, I advise that you take the course at some other time.

5) Class attendance is expected and strongly encouraged. Contact instructor if you have to be

absent so that material, assignments and exams missed by student are to be made up in timely manner.

Civility in the classroom.

Students are expected to assist in maintaining a classroom environment that is conducive to learning. In

order to assure that all students have an opportunity to gain from time spent in class, unless otherwise approved by the instructor, students are prohibited from using cellular phones or beepers, eating or drinking in class, making offensive remarks, reading newspapers, sleeping or engaging in any other form of distraction. Ad hominem remarks or disparaging comments about gender, ethnicity, religion, etcetera will not be tolerated. Inappropriate behavior in the classroom shall result in, minimally, a request to leave the class.

American with Disability Act.

The university is committed to the principle that in no aspect of its programs shall there be differences

in the treatment of persons because of race, creed, national origin, age, sex, or disability, and that equal

opportunity and access to facilities shall be available to all. If you require special accommodations in order to

participate, please contact me, as soon as possible for necessary accommodations. The student should present

appropriate verification from AcessTECH in the office of the Dean of Students. No requirement exists that

accommodation be made prior to completion of this approved university process.

Honor Code.

For those courses where student is assigned to generate reports, literature reviews, and research projects, I take our standards of professional ethics seriously, as I expect all members of the academic community to do. Any form of cheating or plagiarism will result in the receipt of a failing grade for this course. Any paper or class assignment you submit for this class must not have been submitted for any other class. Resubmission of any paper in this class will result in an "F" grade for that paper. No written work may be submitted for academic credit more than once. If you have any questions about how this may apply to a paper you are considering for this class, please ask. You may work in teams but your work that is turned in for credit is entirely the fruit of yours effort and time expenditure.

Tentative Class Schedule Fall 2004

11. Week # 6

Statistics Bibliography

Bruning, J. L., & Kintz, B. L. (1997). Computational Handbook of Statistics. (4th ed.). New York: Longman.

Cody, R. P. & Smith, J. K., (1997). Applied Statistics and the SAS Programming Language. (4th Ed.). Upper Saddle River, NJ: PrenticeHall.

Edwards, A. L. (1985). Multiple Regression and Analysis of Variance and Covariance. (2nd ed.). W. H. Freeman and Company: New York.

Glass, G. V., & Hopkins, K. D. (1984). Statistical Methods in Education and Psychology, (2nd ed.) New Jersey: Prentice-Hall, Inc.

Keppel, G., & Zedeck. S. (1989). Data Analysis for Research Designs. W. H. Freeman and Company: New York.

Kirk, R. E., (1999). Statistics: An Introduction. (4th. Ed.) Fort Worth, TX: HarcourtBraceCollege Publishers.

Kirk, R. E. (1995). Experimental Design: Procedures for the Behavioral Sciences. (3rd ed.). Brooks/Cole Publishing Co.

Lehman, P. W. (1988). Statistical Reasoning for the Behavioral Sciences: Study Guide (2nd ed.). Boston: Allyn and Bacon, Inc.

Marascuilo, L. A., & Serlin, R. C. (1988). Statistical Methods for the Social and Behavioral Sciences. W. H. Freeman and Company: New York.

Pedhazur, E. J. (1982). Multiple Regression in Behavioral Science: Explanation and Prediction. (2nd ed.). Holt, Rinehart and Winston: New York.

Roscoe, R. J. (1975). Fundamental Research Statistics for the Behavioral Sciences. New York: Holt, Rinehart, and Winston, Inc.

Shavelson, R. J. (1988). Statistical Reasoning for the Behavioral Sciences (2nd ed.). Boston: Allyn and Bacon, Inc.

Scheaffer, R. L., W. Mendehall, & Ott, L. Elementary Survey Sampling. (4th Ed.) Belmont, CA: Duxbury Press.

Winer, B. J., Brown, D. R., & Michels, K. M. (1991). Statistical Principles in Experimental Design. (3rd ed.). McGraw-Hill, Inc.: New York.

EPSY 5381 FALL 2004 SEMESTER ROSTER