Introduction to Statistical Analysis

The limited mathematical preparation of the student and the need for some understanding of the theoretical justification of methods of analysis are the two sides of a dilemma that one has to face in writing a textbook in applied statistics. The student in an applied field is not often accustomed to mathematical manipulations, whereas a pure description of statistical methods may very well turn the book into a collection of recipes. The authors of the second edition of Introduction to Statistical Analysis handled this dilemma quite beautifully. Although a student with a meager “knowledge of algebraic addition, subtraction, and multiplication” may not necessarily find all parts of the text easy to follow, most of the arguments are presented with a minimum amount of mathematics but with adequate rationale. The fine treatments of analysis of variance and the Neyman-Pearson theory of testing hypotheses are good examples.