Stats #03: Using SPSS to Develop a Linear Regression Model

Content:  This three hour training class will give you a general introduction in how to use SPSS software to compute linear regression models. Linear regression models provide a good way to examine how various factors influence a continuous outcome measure. There are three steps in a typical linear regression analysis:

1. Fit a crude model
2. Fit an adjusted model
3. Check your assumptions

These steps may not be appropriate for every linear regression analysis, but they do serve as a general guideline. This class will provide hands-on experiences using SPSS software. You will use two SPSS data sets for practice exercises: bf.sav and housing.sav.

Objectives:  In this class you will learn how to:

• interpret the slope and intercept in a linear regression model;
• compute a simple linear regression model; and
• make statistical adjustments for covariates.

Teaching strategies:  Didactic lectures and individual computer exercises.

IRB Education Credits:  This class does not qualify for IRB Education Credits (IRBECs).

Outline:

• Seating in the computer lab
• Overview of the STATS web pages
• Consulting services that I provide
• Installing SPSS terminal server (draft)
• Definition: Categorical data
• Definition: Continuous data
• Description of the breast feeding data set
• Description of the Albuquerque housing data set
• Practice exercises
• Interpreting linear regression coefficients
• Guidelines for linear regression models
• SPSS dialog boxes for linear model examples
• Please fill out an evaluation form