Before you start!

Did you take the Module 1 quiz?!! I hope you did. Especially, the t-test, t-confidence intervals, F-test, and correlation will be frequently used and referred to in this and later modules.

It is strongly recommended that you dig out your old math book, and review some simple concepts, like drawing a line through two points in a (Cartesian) coordinate system; line equation; line slope (positive slope, negative slope, no slope); and y-intercept. Feeling comfortable with these concepts and being able to do those with pencil and paper will greatly help you understand regression.

In addition, the Electronic Textbook (by StatSoft) has lots of material available for your reading and review. From that book, please skim through the following chapters and sections:

Elementary Concepts in Statistics
• Dependent vs. independent variables
• Measurement scales
• Relations between variables
• Why relations between variables are important
• Two basic features of every relation between variables

Basic Statistics

• Correlations
  • What is correlation
  • Simple linear correlation
  • Pearson correlation
  • How to Interpret
    • Positive correlation
    • Negative correlation
  • Significance of correlation
  • Outliers
    • Outliers - more details
    • Scatterplots
  • Quatitative approach
  • Non-homogeneous groups
  • Confidence interval for a regression line

Note: Please recall that the Pearson Correlation coefficient measures the strength of linear relationship between variables. Consequently, outlier data points may cause significant problems especially if the sample sizes are small. Similarly, non-homogeneous groups may cause one to believe that relationships exist, but once data are stratified (or separated into homogenous groups) correlation between variables may completely change. Further, the Pearson Correlation coefficient fails also to detect strong non-linear and polynomial relationships.

Note: Extensive use of graphical tools will help you learn to understand the data under consideration, as well as the relationship between variables. Even just for the fun of it, please plot variables against each other always to learn about their relationship and the magnitude of that relationship. Because of the importance of graphical analysis please review also the following:

Graphical Techniques

• Scatterplots
• Regular scatterplots
• Data reduction
• Graphical breakdown
• Special topics in graphical analytical techniques: Brushing
• Brushing defined

Later in this module reference will be made to these sections.

Also, please remember to turn to the book's very extensive Glossary when you need a short more technical overview of a topic or concepts, or are looking for a definition, and to the Statistical Tables if you need to check critical values for your t- and F-tests.