PSY2001
Course Information Form

2004


Instructor: Dr. D.A. Bors
Office S-638
Phone #: 287-7468

email: bors@utsc.utoronto.ca

Link to Practice Data
Link to Final Assignment data set


For the final assignment, from the data set construct a model for predicting z-scores (grades). Please report all tests of assumptions on the variables included in your final model, include figures where appropriate. Discuss in a paragraph or two any issue or violated assumption that you may encounter. Finally, what important variable might be missing from your model and how might its addition influence your results?

 

 

T.As: Gabriela Husain

Text: Statistcal Methods for Psychology (5th Edition) by David Howell

This course is designed to introduce the student to the General Linear Model and two of its most common expression in psychology: Analysis of Variance and Multiple Regression. Additionally, students will be asked to familiarize themselves with some of the current theoretical issues in the realm of data analysis itself, e.g., the value of testing the null hypothesis.

Grading

There will be three assignments. The First two assignments (20% each) will be due in class two weeks following their formal announcement. The third assignment (30%) will be due the last class meeting. The final assignment (30%) will be due two weeks after the end of classes.

Tentative Course Outline

Week Topic Chapters
1 Review of Descriptive Statistics and Graphs 1 through 7
2 Introduction to ANOVA: Completely Randomized Designs 11
3 Power & Effect Size 8 & 11
4 Introduction to Multiple Comparisons 12
5 Testing Assumptions 11
6 Introduction to Repeated Measures Designs 14
7 Multiple comparisons continued 14
8 Factorial Designs (between-subjects only) 13
9 Factorial Designs ( Mixed designs) 13
10

Inroduction to Multiple Regression

 15
11 Multiple Regression Cont. (Diagnostics) 15
12 Non-parametric Statistics 18

 

Key Overheads Used in Class

LINK to formula for computing the coefficients for test of linear trend.

 

Basic Theorems

Assumption for ANOVA

Structural approach to ANOVA

Randomized Block Designs & Repeated Merasures

Homogeneity of Variance

FMax table

Fixed versus Random Factors

Mixed Design (one between-subject factor and one within-subject factor)

Factorial Designs I

Factorial Designs II

Multiple Comparisons

Regression Analysis: An introduction

Method of Least Squares (Simultaneous equations)

Correlations

Assumptions for regression & correlation

Test of significance for regression and correlation

Introduction to Multiple Regression

What can go wrong with multiple regression?

Walking thorugh a simple case of multiple regression