Psychology 340 Syllabus
Statistics for the Social Sciences


Illinois State University
J. Cooper Cutting
Fall 2005



Contact Information

Instructor: J. Cooper Cutting
Office: De Garmo 443
Phone: 438-2999
e-mail: jccutti@ilstu.edu
office hours: M 11-12, Tu 9-10,
& 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 --- 10%

Students will take 10 quizzes during the semester. These quizzes will be unannounced (e.g., pop quizzes) and either administered in class using paper-and-pencil or using Mallard. The "pop" quizzes are intended to encourage class attendance; if you miss a class in which a pop quiz has been administered, you may be given the opportunity to make-up the quiz by performing additional work. Make-up quizzes will only be allowed for excused absences, will only be given at the discretion of the instructor, and will be limited in number (i.e., no more than two quizzes can be made up; after two have been made up, the student will receive zeroes on missed quizzes).

Exams --- 45%

Three in-class exams will test students' conceptual and mathematical understanding of hypothesis testing. Exam questions will be short answer 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 (e.g., medically unable by doctors written orders, death in the immediate family) or with prior approval of the instructor. You must also contact the instructor as early as it is feasible to arrange an absence from an exam and obtain a make-up exam. If you have valid reason why you cannot take the exam but wait until after the exam, you may not be given a make-up exam if it would have been reasonably possible to contact the instructor earlier. This policy does not mean that you have to have an ambulance pull over to call the instructor if you have a car accident on your way to an exam. You should, however, contact the instructor as soon as it is feasible to do so. Voice-mail and email make doing so very convenient.

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) + 0.10*(quiz average) + 0.45*(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).

Readings:

Required

Optional

Aron, A. & Aron, E. (2003). Statistics for Psychology, 3rd Ed. New York: Prentice Hall.

Textbook's website

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

Topics

Class Dates Tentative topic calendar Readings Lectures Labs Homework
WK1 Aug 22 Introduction and syllabus review. syllabus lecture Lab1
Aug 24 Basic research methodology &
Review of SPSS
SPSS tutorials 1 | 2 lecture Lab2
WK2 Aug 29 Describing Distributions I (Graphically) Chapter 1 lecture Lab3 Homework #1
Due: Wed, Sept 7
Aug 31 Describing Distributions II: Center & Variability Chapter 2 lecture Lab4
WK3 Sept 5
Labor Day
Sept 7 Correlational studies Chapter 3 lecture Lab5 Homework #2
Due: Wed, Sept 14
WK4 Sept 12 Prediction Chapter 4 lecture Lab6 Homework #3
Due: Wed, Sept 21
Homework 3 key
Sept 14 Bi-variate Regression & Multiple regression Chapter 4 lecture Lab7
WK5 Sept 19 Probability and the Normal Distribution Chapters 5 & 6 lecture Lab8 Homework #4
Due: Wed, Sept 28
Sept 21 Hypothesis testing Chapters 5 & 6 lecture Lab9
WK6 Sept 26
Exam 1
Sept 28 Sampling Distributions Chapter 7 lecture Lab10 Homework #5
Due: Wed, Oct 12
WK7 Oct 3 Effect sizes and power I Chapter 8 lecture Lab11
Oct 5 Effect sizes and power II Chapter 8 lecture Lab11
WK8 Oct 10 Hypothesis testing: t-tests I Chapters 9 & 10 lecture Lab13 Homework #6
Due: Wed, Oct 19
Oct12 Hypothesis testing: t-tests II Chapters 9 & 10 lecture Lab14
WK9 Oct 17 Hypothesis testing: t-tests III Chapters 9 & 10 lecture Lab15 Homework #7
Due: Wed, Oct 26
Solutions
Oct 19 Hypothesis testing: t-tests IV Chapters 9 & 10 lecture Lab16
WK10 Oct 24 Hypothesis testing for correlation and regression Chapter 10 lecture Lab17
Oct 26 Hypothesis testing for correlation and regression Chapter 10 lecture Lab18
WK11 Oct 31
Exam 2
Nov 2 Single factor between groups ANOVA Chapter 11 lecture Lab19 Homework #8
Due: Nov. 16
WK12 Nov 7 Single factor between groups ANOVA Chapter 12 lecture Lab20
Nov 9 Single factor Repeated measures ANOVA lecture Lab21
WK13 Nov 14 Single factor Repeated measures ANOVA Research Project lecture Lab22 Homework #9
Due: Nov. 30
Nov 16 Factorial ANOVA Chapter 13 lecture Lab23
WK14 Nov 21
THANKSGIVING - No class
Nov 23
WK15 Nov 28 Factorial ANOVA Chapter 13 lecture Lab24 Homework #10
Due: Dec. 7
Final Project
Due Dec. 12
Nov 30 Mixed design ANOVA   lecture Lab25
WK16 Dec 5 Putting it all together Chapter 16 lecture Work on Final Project  
Dec 7 Review for the final exam   lecture
Finals Week FINAL EXAM
8 AM Wed Dec. 14



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