The first four of the following essays are intended as a review of elementary aspects of basic quantitative data analysis.  I assume readers have taken statistics courses covering univariate and bivariate analysis; this discussion is not an introduction to these methods.  Instead, it reviews this basic material to correct some misconceptions that students frequently seem to have after taking such courses, misconceptions that interfere with their understanding of more advanced methods of analysis, that is, multivariate statistical techniques.  These essays are an accumulation of responses to questions that have arisen in throughout the life of this course on the practical application of multivariate data analysis.  These questions have come from bright students who have mastered the various statistics courses required for their doctoral training, including much more advanced techniques.  These essays, then, are Aneshensel's remedy for statistics as it is usually taught or not.
    Two additional chapters concerning multiple linear regression and logistic regression are also included as a basic review of the practical application of multivariate statistics.

The Basics:
The Person - Variable Matrix
Univariate Analysis: Central Tendency, Spread and Associations
Measurement: Reliability, Validity, and Associations
Bivariate Analysis: Estimating Associations

The Next Level:
Multiple Linear Regression
Logistic Regression