Syllabus


Contact Information

Instructor: J. Cooper Cutting
Office: De Garmo 435 D
Phone: 438-2999
e-mail: jccutti@ilstu.edu
office hours: M 1-2, Tu 2-3,
& by appointment

General course information

Course Overview

This course is designed to cover hypothesis testing in the behavioral sciences, building on concepts learned in PSY/ECO/GEO/POS 138. The logic, assumptions, computation, and interpretation of inferential statistics will be covered, including one-sample, related-samples, and independent-samples t-tests; one-way and two-way ANOVA; correlation and bivariate regression; and non-parametric procedures. In addition to the logic of hypothesis testing, PSY 340 will integrate the use of the software package SPSS as a tool for data management and hypothesis testing. Writing skills will also be developed through a research report and written exam questions.


Course Objectives

As a result of taking PSY 340 students will have the opportunity to apply important quantitative reasoning skills as they relate to research in the behavioral sciences. Specifically, the course will help students develop the following skills and abilities:
  1. Think critically about the use of hypothesis testing in the behavioral sciences.
  2. Choose an appropriate statistical test for specific forms of data and hypotheses.
  3. Understand the logic and mathematical basis for different inferential statistics.
  4. Use computers and the software package SPSS as a tool for data management and hypothesis testing.
  5. Draw valid conclusions about hypotheses from the results of different statistical tests.
  6. Coherently describe conclusions from a hypothesis test in written form.

Department objectives

Evaluating Student Performance

Homework --- 30%

The homework is essential to understanding concepts and practicing skills. Assignments are designed to assess students' knowledge of the specific statistical tests, the application of those tests to specific types of data, and the computation of those tests using SPSS. All homework is to be turned no later than the beginning of class on the due-date. Late work that does not comply with the above policies will still be graded, must still be turned in, but will be given 50% of the possible points at best. In all cases, written documentation may be requested.

Quizzes --- 5%

Students will take 10 quizzes during the semester. These will be administered using Blackboard's quiz capabilities and are intended to encourage reading of the textbook.

Exams --- 50%

Three in-class exams will test students' conceptual and mathematical understanding of hypothesis testing. Exams 1 and 2 are each worth 15%. The final exam is worth 20%. Exam questions will be short answer (including computational questions) in nature, and each and every exam is implicitly and explicitly cumulative! Exams will cover all material covered in lecture and in the textbook. Similar to the homework assignments, make-up exams will be administered only in grave circumstances.

Research Project --- 15%

Each student will complete a research project during the semester. The research project involves: choosing a topic problem and data set from several different data sets available from the instructor, choosing an appropriate statistical test for hypothesis testing for the problem chosen, running the appropriate test(s) using SPSS, interpreting the SPSS output, and writing a paper (roughly five pages) describing the problem and the conclusions from the statistical test results. This project will test students' ability to apply and conduct an inferential statistic to a specific problem of interest. The research report will be written in APA style and laser-printed (or printed with an inkjet printer of similar quality). Blurred printing, smudged printing, or less-than-laser quality printing is unacceptable and will result in a grade of 0. The projects are due on the last day of class; late projects will not be accepted and will be assigned a grade of zero. Additionally, failing to run a spell-check on the assignment will result in losing 10% for each spelling error that would have been caught by a standard spell-checking program.

Extra-credit opportunities

Grading Scale

A weighted grade score will be calculated for each student in which the simple average of all assignments within each category are weighted according to the percentages above and added together:
score = 0.30*(homework average) + 0.05*(quiz average) + 0.50*(exam average) + 0.15*(project)
The total score will be computed and available within the Mallard web page for each student throughout the semester. Grades will be assigned based on the following ranges:
GradePercentage Score Range
A 90 - 100
B 80 - 89.9
C 70 - 79.9
D 60 - 69.9
F 0 - 59.9



Academic Dishonesty

Active participation is the central requirement for the class. Students will be expected to participate in a variety of ways, including several written and oral presentations and discussions. If you are going to miss a class, then you will miss an opportunity for participation. So it is critically important that you notify me AS SOON AS YOU KNOW that youÕll be absent and WHY. Call, e-mail, or talk to me in person. Opportunity to make-up the missed work requires prior notification of the absence and an excused absence (that is one that you instructor accepts as reasonable and legitimate). How and when the work will be made up will be determined by the instructor.

To ensure a smooth flow of discussions, the following policies are established: Students are encouraged to listen with an open mind, respect the contributions of others, and avoid personal attacks. Students will often be faced with alternative viewpoints from the professor or their peers. Thus, students should be prepared to defend their own positions with empirical data, obtained from the assigned readings, and reasoned argument.

You are expected to do your own work. Plagiarism and cheating of any sort will not be tolerated. Either behavior will result in a grade of "F". Note that plagiarism includes situations where you meet with other students for group discussions and are asked write a summary. Unless otherwise instructed, this means that each participant in the group must write their own summary. Making up false excuses for absences will also be considered cheating and may result in a grade of "F" for missed work.

And finally, if you have any questions regarding anything in the syllabus and or the course in general, please feel free to ask. Talk to me in class, via phone, or e-mail. Don't just assume that you know (or should know) the answer, I may not have been clear enough or may have forgotten to mention something.

Accommodations

Illinois State University is an institution and a faculty concerned with helping all of our students feel welcome, and with helping all students learn and develop to their full potential. Any student needing to arrange a reasonable accommodation for a documented disability should contact Disability Concerns at 350 Fell Hall, 438-5853 (voice), 438-8620 (TDD).

Required

Optional

Aron, A., Aron, E., & Coups, E. J. (2006). Statistics for Psychology, 5th Ed. New York: Prentice Hall.

Textbook's website

American Psychological Association. (2001). Publication manual of the American Psychological Association (5thEdition.).Washington, DC: Author.

Class Dates Topic Lectures Lecture Status Reading Lab
WK1 Jan 13 Class cancelled due to illness
Jan 15 ISU cancelled due to cold weather
WK2 Jan 20 Introduction and syllabus review. Introductions new   Lab
Jan 22 Basic research methodology &
Review of SPSS
SPSS review new chpt 1 & web chpt A Lab
WK3 Jan 27 Describing Distributions Describing Distributions I old chpt 2 Lab
Jan 29 Describing Distributions II old Lab
WK4 Feb 3 Probability and the Normal Distribution Hypothesis testing I old chpt 3 Lab
Feb 5 Hypothesis testing Hypothesis testing II old chpt 4 Lab
WK5 Feb 10 Sampling Distributions Sampling distributions old chpt 5 Lab
Feb 12 Effect sizes and power Effect Sizes & Power I old chpt 6 Lab
WK6 Feb 17   Review old   Lab
Feb 19
Exam 1
WK7 Feb 24 Hypothesis testing: t-tests T-tests I old chpt 7 Lab
Feb 26 T-tests II old chpt 8 Lab
WK8 Mar 3 T-tests III old Lab
Mar 5 ANOVA: one-way between groups ANOVA I old chpt 9 Lab
WK9 Mar 17 ANOVA II old Lab
Mar 19 ANOVA: one-way within groups ANOVA III old web chpt B Lab
WK11 Mar 24 ANOVA IV old Lab
Mar 26 Factorial ANOVA ANOVA V old chpt 10 Lab
WK12 Apr 2 ANOVA VI old   Lab
Apr 4

Factorial ANOVA: Mixed designs

ANOVA VII old Lab
WK13 Apr 9
Exam 2
Apr 11 Correlation Correlation old chpt 11
Research project
Lab
WK14 Apr 16    
Apr 18 Prediction: Bi-variate regression Regression I old chpt 12 Lab
WK15 Apr 23 Prediction: Multiple regression Regression II Lab
Apr 25 Hypothesis testing for correlation and regression Regression III old Lab
WK16 Apr 30 Hypothesis testing for correlation and regression     chpt 12 Lab
May 2 Putting it all together General Linear Model old chpt 15 (618-622)
web chpt C
 


If you have any questions, please feel free to contact me at jccutti@ilstu.edu.