Introduction to Statistics and Data Analysis

With Exercises, Solutions and Applications in R

  • Christian Heumann
  • Michael Schomaker
  • Shalabh

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Descriptive Statistics

    1. Front Matter
      Pages 1-1
    2. Christian Heumann, Michael Schomaker, Shalabh
      Pages 3-15
    3. Christian Heumann, Michael Schomaker, Shalabh
      Pages 17-35
    4. Christian Heumann, Michael Schomaker, Shalabh
      Pages 37-66
    5. Christian Heumann, Michael Schomaker, Shalabh
      Pages 67-94
  3. Probability Calculus

    1. Front Matter
      Pages 95-95
    2. Christian Heumann, Michael Schomaker, Shalabh
      Pages 97-107
    3. Christian Heumann, Michael Schomaker, Shalabh
      Pages 109-125
    4. Christian Heumann, Michael Schomaker, Shalabh
      Pages 127-152
    5. Christian Heumann, Michael Schomaker, Shalabh
      Pages 153-178
  4. Inductive Statistics

    1. Front Matter
      Pages 179-179
    2. Christian Heumann, Michael Schomaker, Shalabh
      Pages 181-208
    3. Christian Heumann, Michael Schomaker, Shalabh
      Pages 209-247
    4. Christian Heumann, Michael Schomaker, Shalabh
      Pages 249-295
  5. Back Matter
    Pages 297-456

About this book

Introduction

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital.

The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

Keywords

descriptive statistical methods inductive statistical methods quantitative data analysis statistical software R introduction to statistics explorative statistical methods applications of statistical methods probability distributions statistical inference hypotheses testing linear regression random variables graphical representation of data

Authors and affiliations

  • Christian Heumann
    • 1
  • Michael Schomaker
    • 2
  • Shalabh
    • 3
  1. 1.Department of StatisticsLudwig-Maximilians-Universität MünchenMünchenGermany
  2. 2.Centre for Infectious Disease Epidemiology and ResearchUniversity of Cape TownCape TownSouth Africa
  3. 3.Department of Mathematics and StatisticsIndian Institute of Technology KanpurKanpurIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-46162-5
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-46160-1
  • Online ISBN 978-3-319-46162-5
  • About this book