COURSE SYLLABUS for PSY 340
Statistics for the Social Sciences

Illinois State University
Department of Psychology
Spring, 2004

Section 02 --- Tu & Th from 11:00am to 12:15pm in DEG 13

Instructor

Dr. Matthew Hesson-McInnis

Office415 DeGarmo Hall
Phone(309) 438-7266
Emailmshesso@ilstu.edu
Web Pagehttp://www.ilstu.edu/~mshesso

Office Hours

Wednesdays 2:00pm to 4:00pm
or by appointment

Course Web Page
http://www.ilstu.edu/~mshesso/Classes/Psy340/psych340.html

Mallard Web Page
https://mallard.ilstu.edu/psy340/




Course Overview

Course Catalogue Entry

Prerequisite: PSY/ECO/GEO/POS 138 (not for credit if had PSY 240 or PSY 345)
3 Semester Hours

Advanced statistical techniques for the behavioral sciences including hypothesis testing, inferential statistics, and data analysis using SPSS.

Course Description

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 correlation and bivariate regression; one-sample, paired-samples, and independent-samples t-tests; and one-way and two-way ANOVA. 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 open-ended exam questions.

Course Prerequisite

Students who have met the course prerequisitive other than through PSY/ECO/GEO/POS 138 are strongly encouraged to meet with the instructor to develop a plan to address deficiencies in skills typically gained during this prerequisite course. Students who took the 138 course are, of course, also welcome to meet with the instructor to develop a plan to brush up on their skills if they so desire. One component of such a plan are self-paced tutorial sessions on using SPSS. This lab (DEG 13) will be available, as will a teaching assistant, on most Friday afternoons throughout the semester. Specific schedules will be posted.

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.

Accommodations

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). Students who ask the instructor for special accommodations based on disabilities must work with Disability Concerns to assess and document their needs.


Readings

Required Readings

Suggested Readings




Evaluating Student Performance

Exams --- 40%

Three in-class exams will test students' conceptual and mathematical understanding of hypothesis testing. Each exam is implicitly and explicitly cumulative! Exams will cover all material covered in lecture, on assignments, and in the textbook. Make-up exams will be administered only in grave circumstances (e.g., medically unable by doctors written orders, death in the immediate family) and only with prior approval of the instructor (one day in advance) if humanly possible.

Research Project --- 20%

Each student will complete a research project during the semester. The research project involves: (a) choosing a topic problem and data set from a list available from the web page, (b) choosing one or more appropriate statistical tests for hypothesis testing for the problem chosen, (c) running the appropriate test(s) using SPSS, (d) interpreting the SPSS output, (e) and writing the results and discussion section of a paper in APA style (roughly five to seven pages) describing the problem and the conclusions from the statistical test results. This project will assess students' ability to apply and conduct inferential statistics to address a specific problem of interest. Further details are available on the course web page. The research project will not be accepted after the due date without prior arrangement with the instructor.

Homework --- 30%

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. Completing these assignments is essential to understanding concepts and developing practical skills. Some homework assignments will require being hand written or word processed; these assignments will be due at the beginning of class on the due-date of the assignment. Other assignments will require using Mallard to complete a series of questions; these assignments are due as indicated on the Mallard Web site, and the same policies as outlined for quizzes (see below) will apply. Late work will not be accepted unless an arrangement has been worked out with the instructor at least one day prior to the due date.

Quizzes --- 10%

Students will take a short quiz using Mallard, covering key concepts from assigned textbook readings. The readings are expected to be completed prior to the beginning of lecture on a given topic; thus, each quiz will be due on the date that the topic will begin. The quizzes cover the reading of the textbook rather than lectures. Quizzes may be repeated up to 10 times for full credit (with deductions for each attempt after 10), and there will be a cumulative 10% deduction per day for lateness (e.g., if the quiz is submitted not more than 24 hours past the due date, it will be considered 1 day late with 10% penalty; if the quiz is submitted more than 24 hours but less than 48 hours, then it is two days late, with a 20% deduction, and so forth).

Course Letter Grades

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 = 0.40*(exam average) + 0.30*(homework average) + 0.20*(project) + 0.10*(quiz average)

The total score will be computed and available within the Mallard web page for each student throughout the semester. Scores at or above 90.00% will earn an "A"; scores below 90.00% but at or above 80.00% will earn a "B"; scores below 80.00% but at or above 70.00% will earn a "C"; scores below 70.00% but at or above 60.00% will earn a "D"; and scores below 60.00% will earn an "F". It is important to note that Mallard computes the total course score with floating-point precision, although only two decimal places are displayed. Thus, the only rounding that will occur will be in the third decimal place. For example, an 89.995 would be rounded to 90.00 for the course score, earning an A for the course grade. A score of 89.994, however, would round to 89.99 for the course score, earning a B for the course grade.

Extra Credit

Extra credit will be offered in this course with two possibilities.

Grading Appeals

Students occasionally disagree with the evaluation of their work. Any student who believes that his or her work deserves additional points may appeal the grade for any course assignment (including homework, quizzes, exams, and the course project). To appeal an assignment grade, the student should return the assignment along with an explanation of why he or she believes additional points are merited, not to exceed one page. Students should keep in mind, however, that each assignment asks for the best answer to each question, and answers that may be technically correct but are not the best answer may not be awarded full points. If there is a clerical error in adding points for an assignment or a data-entry error in the Mallard grade book, students do not need to file an appeal. They may simply stop by with the graded work during office hours and ask to have the error corrected. These appeals must be received within one week of the assignment being returned.

It is also important to note that course letter grades are not negotiable under any circumstances. Grades are earned by the student rather than given by the instructor. Course letter grades are determined by the formula and criteria stated above. Please do not ask the instructor to assign a better grade for the course, to offer individual extra credit opportunities, or to make exceptions to these grading policies.


Tentative Class Schedule and Topics Covered

DateTopic (linked to lecture notes)Readings (linked to textbook extras)
1/13 - 1/15 Introduction to the course, SPSS, Mallard, and research methods N/A
1/20 - 1/22 Review of central tendency, variability, and z-scores Aron & Aron, Ch. 2
1/27 - 1/29 Review of correlation Aron & Aron, Ch. 3
2/3 - 2/5 Review of regression and prediction Aron & Aron, Ch. 4
2/10 - 2/17 The normal distribution and hypothesis testing Aron & Aron, Ch. 5 & Ch. 6
2/19 Exam 1 Aron & Aron, Ch. 2 - 6
2/24 Sampling Distributions Aron & Aron, Ch. 7
2/26 - 3/2 Effect sizes and power Aron & Aron, Ch. 8
3/4 - 3/16 One-sample and paired-sample t-tests Aron & Aron, Ch. 9
3/18 - 3/23 Independent samples t-tests Aron & Aron, Ch. 10
3/25 Hypothesis testing for correlation and regression ***
3/30 Exam 2 Aron & Aron, Ch. 2 - 10
4/1 - 4/6 Analysis of Variance (ANOVA) Basic concepts Aron & Aron, Ch. 11
4/8 - 4/13 One-way ANOVA: Computation Aron & Aron, Ch. 12
4/15 - 4/22 Two-way ANOVA: Basic concepts Aron & Aron, Ch. 13
4/27 - 4/29 Additional Topics and the General Linear Model Aron & Aron, Ch. 16
5/6 Final Exam (i.e., Exam 3) Thursday at 10:00am - 12:00pm Aron & Aron, Ch. 2 - 13 & 16



Academic Integrity

Students are expected to live up to Illinois State University's standards for academic integrity. If you have not read the university's policies and definitions of academic integrity, you should do so (see the course catalogue). In addition to those policies, the following policies will apply to this course.

Instances of academic dishonesty of any form will be treated seriously and harshly. Academic dishonesty includes, but is not limited to, plagiarism (representing someone else's ideas or words as your own), cheating on an exam, or copying homework assignments. Additionally, making false statements to make-up an assignment or exam, to obtain any kind of extension on course work, or to obtain any kind of special consideration of any policy will constitute cheating and will be treated as such under this policy. This policy should not, however, be construed as a prohibition of students working collaboratively on homework assignments. Although there is a fine line between collaboration and plagiarism, please keep in mind that assignments are turned in with a single name and should represent the work product of a single person's efforts. Discussing a general approach to a problem or checking answers is acceptable, but copying of work or otherwise presenting another person's work as one's own is a violation.

Any student who engages in academic dishonesty or allows it to occur will be subjected to one or more of the following consequences depending on the severity of the offense, at the sole discretion of the instructor: receiving a zero on the assignment in question; receiving the next lower letter grade than otherwise earned for the course; receiving a letter grade of "F" for the course; referral to the student judicial process (the consequences of which include disciplinary probation, suspension from coursework, or dismissal from the university).

Additionally, students have the responsibility to prevent others from copying their work for the course. Should evidence of such copying come to light, all parties involved in each incident will share the same consequences. Allowing someone to copy your work compromises the integrity of the evaluation and constitutes dishonest academic behavior.

Finally, all students are expected to conduct themselves in the classroom in a polite and respectful manner and in accordance with the student code of conduct. I expect all students to respect their colleagues by not behaving in any way that disrupts the classroom or makes it difficult for others to participate in class. Students who need to leave early are expected to sit close to the door and leave quietly. Likewise, students who arrive late are expected to sit in the most easily accessible seat and not climb over backpacks and books to sit in a particular seat.



Last modified Monday, January 12, 2004 6:58 PM