Home Student Resources Chapter 20 – Regression methods

Chapter 20 – Regression methods

This chapter introduces the readers to the process of predicting values of a ‘criterion’ variable from values of a ‘predictor’ variable.

Exercises

Exercise 20.1

Multiple regression practice

The data set for the multiple regression analysis conducted in the book is called multiple regression data (book).sav and a link to this file is provided below.

A further exercise in multiple regression can be performed using the file multiple regression ex.sav, which is also provided below. Imagine here that an occupational psychologist has measured ambition, work attitude and absences over the last year and used these to predict productivity over the last three months. If there is good predictive power the set of tests might be used in the selection process for new employees.

Click the label above to obtain the SPSS data sheet for this exercise.

In this exercise, please perform the multiple regression analysis in SPSS if you have the programme and then answer the following multiple choice questions:

Exercise 20.2

<Insert Download Logistic Regression Book Data here>


This link from Chapter 19 also gives you the regression line and residuals:

Correlation and Regression (bfwpub.com)        

and so does this. Take your pick:

Interactivate: Regression (shodor.org)

For an explanation of the logit function and why it is appropriate try:

What is a Logit Function and Why Use Logistic Regression? (theanalysisfactor.com)

An annotated explanation of all the detail in an SPSS logistic regression output:

Logistic Regression | SPSS Annotated Output (ucla.edu)

For detail on linear and multiple regression try:

Mod 2 – Simple Reg (restore.ac.uk)

For detail on logistic regression try:

Mod 4 – Log Reg (restore.ac.uk)