Psychology 343
Statistical Methods in Psychological Science
Statistical Methods in Psychological Science | CRN 95144

   

info & policies | updates | schedule & notes

Instructor
R. Chris Fraley, Ph.D.
Department of Psychology, Behavioral Sciences Building (BSB)
Office: 1050 "A" Office hours: M, W 2:00 - 3:00
E-mail: fraley@uic.edu

Teaching Assistants
Ben Jee | bendj@uic.edu

Ed Sargis | esargis@uic.edu

Location & Time

2219 EPASW | Lecture: Mondays & Wednesdays, 11:00 am - 11:50 am

Note: The class was originally scheduled for 166 DHSP (on the corner of S. Paulina and Rosevelt. The class has moved, however, to 2219 EPASW--the College of Education at the corner of Harrison and Morgan. The first class will be held on Wed, Jan 14th. I placed two notes on the door outside of 166 DHSP on Monday, Jan 12th, so I expect all students to be in the correct room on Wed; I am assuming you made an attempt to attend the first class.

There will be a weekly lab section to accompany the course. Each student should register (if you have not done so already) for one of the following sections:

Lab section
CRN
When
Where
1
95157
Fri, 11:00 - 11:50
0100 SH
2
95125
Fri, 12:00 - 12:50
0100 SH
3
95074
Fri, 10:00 - 10:50
0100 SH

Labs will begin the thrid week of class (Jan 26). Lab attendance is mandatory.

Class webpage: http://www.uic.edu/classes/psych/psych343f/spring2004

Books & Materials

Phillips, J. L. (1999). How to think about statistics (4th - 6th Editions.). New York, NY: W. H. Freeman. [Strongly recommended, but not required. This book is an excellent one for people who may be feeling a bit of math anxiety.]

Please obtain an inexpensive calculator (one that allows you to do square roots easily). You will need to bring it to sections and class. If you already own a calculator, please bring it to class and lab.

Overview of Course

The objective of this class is to provide you with a better understanding of the ways in which mathematics and statistics can be used to deepen our understanding of psychological phenomena.

The lectures will primarily focus on the concepts and ideas underlying quantitative methods in psychology. The lab/discussion sections will give you the opportunity to gain "hands-on" experience in working through specific quantitative problems.

Important Notes Regarding the Class Webpage

I will post lecture overheads on the class web page within the hour following each lecture. I plan to post the overheads online because I want you to spend your class time listening and thinking carefully, not copying notes from the board or overhead. If class attendance begins to decline, I will discontinue web notes. You will be able to access the lecture overheads by clicking on the links in the lecture schedule below. If you have PowerPoint on your computer, you can download the actual PowerPoint file from which the overheads originate by right-clicking the PowerPoint link and "saving target as" to your computer.

I realize that it would probably be more useful to you if the overheads were available before lecture. Unfortunately, I often revise my lectures right up to the last minute, so I won't be able to post the notes before class. I have used the "after class" approach in the past, however, and students seem to find it useful to take very brief notes (e.g., key words, questions, reminders) during the actual lecture, and then supplement those notes by printing and rereading the overheads after class.

You should treat the class web page as your primary syllabus. I will post reading assignments, lecture notes, practice test questions, answers to exams you've taken, and exam grades to date on the class web page.

If you do not have Internet access at home, please visit one of the many student computer facilities on campus on a regular basis.

Grading & My Teaching Philosophy

Statistics courses are often dreaded by psychology majors. As a general rule, many students decide to major in psychology because they are not attracted to the quantitative demands of other sciences.

I suspect that one reason why many students are turned off by mathematics and statistics is that that they have never had the opportunity to think critically and intuitively about mathematics. It is not uncommon for students to have learned math in a context in which they were forced to memorize equations or solve math problems incessantly. In this course, my goal is to help you appreciate the kinds of theoretical and applied problems that certain mathematical and statistical tools are designed to solve. By approaching the topic in this manner, I hope to give you a better understanding of how the techniques work, what they mean, and why the study of mathematics and statistics can be exciting. ;-)

There will be four required exams over the course of the semester. These exams will not be cumulative in the strict sense of the term, but the subject matter will build on itself, so mastering material for the second exam, for example, may require that you keep yourself refreshed on earlier material.

If you are unhappy with one of your four exam grades, you can take the optional final and use that grade as a substitute for your lowest of the required four exams. The final exam, however, will be cumulative in the strict sense of the term; I will ask you about anything that has been covered in the course. You will be allowed to substitute the optional final exam score for only one of your exams.

Why do I have this "optional final exam" policy? I allow this because emergencies (e.g., death in the family, oversleeping on exam day, traffic problems) will crop up at some point during the semester, and you might have to miss an exam. I do not give traditional make-up exams under any circumstances; the fact that you can take the optional final and use that grade for your lowest of the four required exams covers all make-up exam situations.

In light of this policy, your best strategy is to plan to study hard for each exam and hope nothing bad happens. Then, if something bad does happen along the way (e.g., decapitation in a cooking accident), you'll know that you can take the optional final and substitute that grade for your missed exam. If you oversleep for exam 1 and then a relative dies for exam 2, you can use the optional final as a substitute for only one of your two zero's. (If you have a genuine medical emergency, the university will sometimes allow for make-up exams. In such an event, it is necessary that you provide me with a copy of your medical bill. A simple doctor's note will not be accepted.)

The exam schedule for the semester is posted on the class webpage. It will not be changed, so please determine as soon as possible whether your schedule will prohibit you from making it to certain exams. It might be wise for you to drop the class (or change to another section) if you can foresee possible problems in scheduling from Day 1.

At least once a week in lecture (either on Mondays or Wednesdays), I will give you a five-minute pop quiz at the beginning of class. These quizzes will be administered at exactly 11:00 a.m. and will be collected at 11:05 a.m. I strongly encourage you to come to class on time; there will be no make-up pop quiz opportunities. These quizzes will not be difficult. My objective in administering these quizzes to encourage you to keep up with the readings and the lecture material so you don't have to cram at the last minute for the exams.

Of your four highest exam scores, they will be averaged, and that average will account for 60% of your grade. The remaining 40% of your grade will come from lab activities and homeworks (20%) and weekly quizzes (20%). Attendance is required for the labs.

Note: If you need to know your discussion section grade at any point in the semester, please contact your TA.

Note: I do not "curve" exam scores. I use the standard "10% rule" for assigning letter grades (e.g., A = 90% - 100%, B = 80% - 89%). It is possible for everyone to earn an A in my class, but it won't be easy. If everyone does earn an A in my class, I will be thrilled and eat cake for a week.

Students with disabilities who require accommodations for access and participation in this course must be registered with the Office of Disability Services (ODS). Please contact ODS at 312/413-2103 or 312/413-0123.

Updates

Updates will be posted here.

Jan 12, 2004
The class was originally scheduled for 166 DHSP (on the corner of S. Paulina and Rosevelt. The class has moved, however, to 2219 EPASW--the College of Education at the corner of Harrison and Morgan. The first class will be held on Wed, Jan 14th. I placed two notes on the door outside of 166 DHSP on Monday, Jan 12th, so I expect all students to be in the correct room on Wed; I am assuming you made an attempt to attend the first class.

Jan 26, 2004
Lab sections will begin next week (the week of Feb 2nd). I'm pushing the lab back a week because I won't be in town this week. In addition, the first exam will be on Feb 4th instead of Feb 2nd. The first exam will be a take-home exam and will be due in class the following Monday (Feb 9th). We will have a regular lecture on Wed the 4th.

Feb 11, 2004
I'm going to cancel class today. My cold has moved into my throat and I can barely speak. Sections/labs will still be held this week. See you on Monday.

March 11, 2004
I have posted a homework assignment on-line here. This is due in section next week (March 19th).

March 15, 2004
The grades to date (exams 1 & 2 and the first three quizes) are posted here.

March 15, 2004
Ed Sargis made a handout for the problem you were working on in last Friday's section. Please use this to check over your answers.

April 17, 2004
The grades to date are posted here.

April 19, 2004
I made an error on the board today in class. We should not have taken the sqaure-root of N during the last few minutes. The on-line lecture notes for today's lecture are correct. [Actually, I messed those up too. I've corrected them now. April 21, 2004, 12:30 p.m.]

April 19, 2004
I have posted the horoscope data here. This homework assignment is due on Friday in sections.

April 21, 2004
Some ANOVA exercises are available here. You should practice these on your own time; they will not be due in section.

April 29, 2004
Exam 4 grades and grades to date are posted here. The page this link goes to will be updated as needed; I won't post updates here.

May 6, 2004
Final grades are posted here. The page this link goes to will be updated as needed; I won't post updates here. Have a nice summer!

info & policies | updates | schedule & notes

 

   

Schedule of Lectures, and Exams

Part 1

Quantitative Methods for Measurement and the Description of Distributions
How can we use mathematics and statistics to measure psychological phenomena? How can we summarize the properties of our measurements in an intuitive and efficient manner?

Lecture 1 (Jan 14, 2004): The Use of Mathematics and Statistics to Understand Natural Systems
[PowerPoint download]
Note: To download the slides, simply right-click on the link labeled "PowerPoint download" and choose the option "save target as." Save the file to your computer or disc and open the file in PowerPoint to print the slides.

Lecture 2 (Jan 21, 2004): Quantification and Scales of Measurement
[PowerPoint download]

Lecture 3 (Jan 26, 2004): Visually Summarizing Score Distributions
[PowerPoint download]

January 19 - Martin Luther King, Jr. Day; no classes
January 28 - no class; I'll be away at a conference

Lecture 4 (Feb 2, 2004): Quantifying the Central Tendency of Score Distributions
[PowerPoint download]

Lecture 5 (Feb 4, 2004): Quantifying the Spread or Dispersion of Scores
[PowerPoint download]

Exam 1: Feb 4, 2004 (take home; due Feb 9th) [click here to view or print the exam]

Lecture 6 (Feb 9, 2004): Comparing Scores Across Different Variables: Standardization and Z-Scores
[PowerPoint download]


Part 2

Quantitative Methods for Theoretical Modeling
Many theoretical models can be formalized mathematically. In this section, we will discuss how to formulate simple mathematical-statistical models of psychological processes and estimate the parameters of those models.

Feb 11, 2004 -- Class canceled (see updates)

Lecture 7 (Feb 16, 2004): Quantifiying the Association Between Two Variables: Covariance
[PowerPoint download]

Lecture 8 (Feb 18, 2004): Quantifiying the Association Between Two Variables: Correlation
[PowerPoint download]

Lecture 9 (Feb 23, 2004): Theoretical Models: Quantifying the Mathematical Relationship Between Two or More Variables
[PowerPoint download]

Lecture 10 (Feb 25, 2004): Least-Squares: Estimating the Parameters of Simple Linear Models
[PowerPoint download]

Exam 2: March 3, 2004

Lecture 10.5 (March 8, 2004): Least-Squares: Estimating the Parameters of Simple Linear Models
[we continued the notes from Feb 25]

Lecture 11 (March 10, 2004): Evaluating Model Fit: R-Squared
[PowerPoint download]

Lecture 12 (March 15, 2004): Evaluating Model Fit: Using R-squared to Compare Alternative Models
[PowerPoint download]


Part 3

Using Quantitative Methods to Test and Evaluate Theoretical Models
How do we determine whether a theoretical model provides an adequate account of a psychological process? In this section we will discuss quantitative methods for evaluating and testing theoretical models. We will focus on three reasons why a theoretical model may not fit the data: (a) errors in measurement, (b) sampling errors, and (c) errors in the model itself. Moreover, we will discuss classic techniques for handling the problem of sampling error (i.e., null hypothesis significance tests), their limitations, and modern solutions.

Lecture 13 (March 17, 2004): Explaining Residual Variance: Errors in Models and Errors in Measurement Precision
[PowerPoint download]

Lecture 14 (March 29, 2004): The Problem of Sampling Error: An Intuitive Exploration of the Problem
[PowerPoint download]

Lecture 15 (March31, 2004): Quantifying Sampling Error: The Standard Error of the Mean
[PowerPoint download]

Exam 3: April 7, 2004

Lecture 16 (April 12, 2004): Null Hypothesis Significance Tests: Using Sampling Distributions to Make Decisions about Sampling Error [PowerPoint download]

Lecture 17 (April 14, 2004): Null Hypothesis Significance Tests: t-tests
[PowerPoint download]

Lecture 18 (April 19, 2004): Null Hypothesis Significance Tests: ANOVA
[PowerPoint download] [note: there was an error in the PowerPoint notes that has been corrected on April 21, 2004, around 12:18 p.m.]

Lecture 19 (April 21, 2004): Null Hypothesis Significance Tests: ANOVA example
[PowerPoint download]

Lecture 20 (April 21, 2004): Null Hypothesis Significance Tests: Chi-square [Ed Sargis will give this lecture in discussion sections on Friday, April 23, 2004]
[PowerPoint download]

Lecture 21 (April 26, 2004): Null Hypothesis Significance Tests: Decision Errors, Statistical Power, and Controlling the Error Rate [PowerPoint download]

Exam 4: April 28, 2004

Final Exam:Thursday May 6th 10:30 - 12:30 room 2219 EPASW
See http://www.uic.edu/depts/oar/rr/finals.shtml for information on final exam conflicts.

info & policies | updates | schedule & notes