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Stat Labs

Mathematical Statistics Through Applications

  • Deborah Nolan
  • Terry Speed

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

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Pages 75-98
  3. Pages 139-159
  4. Pages 161-178
  5. Pages 179-195
  6. Pages 237-250
  7. Back Matter
    Pages 251-283

About this book

Introduction

This book uses a model we have developed for teaching mathematical statistics through in depth case studies. Traditional statistics texts have many small numer ical examples in each chapter to illustrate a topic in statistical theory. Here, we instead make a case study the centerpiece of each chapter. The case studies, which we call labs, raise interesting scienti?c questions, and ?guring out how to answer a question is the starting point for developing statistical theory. The labs are substan tial exercises; they have nontrivial solutions that leave room for different analyses of the data. In addition to providing the framework and motivation for studying topics in mathematical statistics, the labs help students develop statistical thinking. We feel that this approach integrates theoretical and applied statistics in a way not commonly encountered in an undergraduate text. The Student The book is intended for a course in mathematical statistics for juniors and seniors. We assume that students have had one year of calculus, including Taylor series, and a course in probability. We do not assume students have experience with statistical software so we incorporate lessons into our course on how to use the software.

Keywords

STATISTICA bioinformatics data analysis linear optimization mathematical statistics statistics

Authors and affiliations

  • Deborah Nolan
    • 1
  • Terry Speed
    • 1
  1. 1.Department of StatisticsUniversity of California, BerkeleyBerkeleyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b98875
  • Copyright Information Springer-Verlag New York, Inc. 2000
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98974-7
  • Online ISBN 978-0-387-22743-6
  • Series Print ISSN 1431-875X
  • Buy this book on publisher's site