Prescriptions for Working Statisticians

  • Albert Madansky

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

Table of contents

  1. Front Matter
    Pages i-xix
  2. Albert Madansky
    Pages 14-55
  3. Albert Madansky
    Pages 56-91
  4. Albert Madansky
    Pages 92-119
  5. Albert Madansky
    Pages 120-147
  6. Albert Madansky
    Pages 148-180
  7. Albert Madansky
    Pages 214-251
  8. Albert Madansky
    Pages 252-287
  9. Back Matter
    Pages 289-295

About this book

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

Authors and affiliations

  • Albert Madansky
    • 1
  1. 1.Graduate School of BusinessUniversity of ChicagoChicagoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-3794-5
  • Copyright Information Springer-Verlag New York 1988
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-8354-6
  • Online ISBN 978-1-4612-3794-5
  • Series Print ISSN 1431-875X
  • About this book