Correlation and Regression
Linear regression is one of the essential tools in statistical analysis. In this course, we'll walk through step-by-step how to conduct many important analyses using SPSS.
Although you will learn the basics of what these statistics are, we'll avoid complicated mathematical discussions and go right to what you need to know to conduct these analyses.
Linear regression is basically a tool that allows you to test relationships between many variables at the same time, control for variables' effects, and create simple statistical models that allow you to make predictions.
In this course, we'll cover the following key topics:
Correlations: You probably already know this, but understanding how to test the correlation between two variables gets us started in this course.
Simple Linear Regression: Taking correlations one step further by creating a statistical model.
Multiple Linear Regression: Being able to test multiple predictors at the same time and testing the unique effect of each.
Hierarchical Linear Regression: How to test for the influence of different variables by adding them to the model one at a time.
Interaction Analysis: How to test whether there's a two-way interaction between variables (also known as a "moderator" analysis)
These days many employees, during work hours, spend time on the Internet doing personal things, things not related to their work. This is called “cyberloafing.” Research at ECU, by Mike Sage, graduate student in Industrial/Organizational Psychology, has related the frequency of cyberloafing to personality and age.
Logistic regression is used to predict a categorical (usually dichotomous) variable from a set of predictor variables.
As an example of the use of logistic regression in psychological research, consider the research done by Wuensch and Poteat and published in the Journal of Social Behavior and Personality, 1998, 13, 139-150.
This is real data file condensed from a study conducted to explore the prevalence and impact of sleep problems on various aspects of people's lives. Staff from a university in Melbourne, Australia were invited to complete a questionnaire containing questions about their sleep behaviour (e.g. hours slept per night), sleep problems (e.g. difficulty getting to sleep) and the impact that these problems have on aspects of their lives (work, driving, relationships). The sample consisted of 271 respondents (55% female, 45% male) ranging in age from 18 to 84 years (mean=44yrs).