Introduction to Statistics and Data Analysis

With Exercises, Solutions and Applications in R

A textbook by Christian Heumann, Michael Schomaker and Shalabh

Update: The second edition, published in 2023, is now available here


About the book

This introductory statistics textbook is primarily intended for undergraduate students and self-learners. It contains a comprehensive and thorough overview of fundamental statistical concepts such as hypothesis testing, (causal) inference and regression; but also an introduction into descriptive statistics and graphs. Each chapter is accompanied by a wealth of exercises and solutions. The implementation of the introduced methods are illustrated with .

The second edition can be downloaded from Springer here. The first edition of the book has been downloaded more than 5.4 million times.



Materials

There are some additional materials available for our book.

First edition:

  • The solutions to the exercises of all 11 chapters is available here.
  • All data sets used in the book are contained in this zip-file.

Second edition:

  • The solutions to the exercises of all 14 chapters, as well as all data sets, are available here.

Errata

A list of errata and corrections has been summarized in this document (currently: only first edition).



About the authors

Christian Heumann is a professor at the Ludwig-Maximilian-Universität München, Germany, where he teaches students in Bachelor and Master programs offered by the Department of Statistics, as well as undergraduate students in the Bachelor of Science programs in business administration and economics. His research interests include statistical modeling, computational statistics and all aspects of missing data.
Shalabh is a professor at the Indian Institute of Technology Kanpur, India. He received his Ph.D. from the University of Lucknow (India) and completed his post-doctoral work at the University of Pittsburgh (USA) and University of Munich (Germany). He has over twenty years experience in teaching and research. His main research areas are linear models, regression analysis, econometrics, measurement error models, missing data models and sampling theory
Michael Schomaker is Heisenberg-Professor for Biostatistics at the Department of Statistics, Ludwig-Maximilains University, Munich, Germany. He has taught undergraduate students from the business and medical sciences for many years and has written contributions for various introductory textbooks. His research focuses on missing data, causal inference, model averaging and HIV/AIDS.
For feedback, or reporting errors, please write an email to us. We are currently planning a third extended edition and appreciate any sorts of comments and ideas.