# Prescriptions for Working Statisticians

Book

Part of the Springer Texts in Statistics book series (STS)

1. Front Matter
Pages i-xix
Pages 1-13
Pages 14-55
Pages 56-91
Pages 92-119
Pages 120-147
Pages 148-180
Pages 181-213
Pages 214-251
Pages 252-287
11. Back Matter
Pages 289-295

### Introduction

The first course in statistics, no matter how "good" or "long" it is, typically covers inferential procedures which are valid only if a number of preconditions are satisfied by the data. For example, students are taught about regression procedures valid only if the true residuals are independent, homoscedastic, and normally distributed. But they do not learn how to check for indepen­ dence, homoscedasticity, or normality, and certainly do not learn how to adjust their data and/or model so that these assumptions are met. To help this student out! I designed a second course, containing a collec­ tion of statistical diagnostics and prescriptions necessary for the applied statistician so that he can deal with the realities of inference from data, and not merely with the kind of classroom problems where all the data satisfy the assumptions associated with the technique to be taught. At the same time I realized that I was writing a book for a wider audience, namely all those away from the classroom whose formal statistics education ended with such a course and who apply statistical techniques to data.

### Keywords

Boxplot Variance analysis of variance normal distribution statistics