Applying Contemporary Statistical Techniques

by Rand R. Wilcox

Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.

* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques * Covers many contemporary ANOVA (analysis of variance) and regression methods not found in other books

680 pages, Hardcover

First published December 1, 2002

Reviews

[Yi · Rating 2 out of 5]

This book was very difficult to read, despite the author's claim about no previous training. It presents formulas without providing intuitive reasoning.

I did learn why conventional statistical methods assume normal distribution, which I didn't from other books. It's because even a slight deviation from the normal curve can change the probability distribution, upon which most of the important tests like the t test and ANOVA depend. A contaminated normal curve has higher probabilities at the extremes, so for a hypothesis test to be significant (say, p <) .05, it would require a larger critical value.

But later chapters were too tedious. Now, if only I could get an intuitive account of newer methods and the flaws of conventional methods.