Skip to main content
  • Textbook
  • © 2016

Introduction to Statistics and Data Analysis

With Exercises, Solutions and Applications in R

  • Introduces undergraduate students to quantitative data analysis and statistics

  • Includes a wealth of examples, exercises and solutions

  • Features working computer code in the statistical software R

  • Includes supplementary material: sn.pub/extras

Buying options

eBook USD 59.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-46162-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 74.99
Price excludes VAT (USA)
Hardcover Book USD 119.99
Price excludes VAT (USA)

This is a preview of subscription content, access via your institution.

Table of contents (11 chapters)

  1. Front Matter

    Pages i-xiii
  2. Descriptive Statistics

    1. Front Matter

      Pages 1-1
    2. Introduction and Framework

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 3-15
    3. Frequency Measures and Graphical Representation of Data

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 17-35
    4. Measures of Central Tendency and Dispersion

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 37-66
    5. Association of Two Variables

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 67-94
  3. Probability Calculus

    1. Front Matter

      Pages 95-95
    2. Combinatorics

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 97-107
    3. Elements of Probability Theory

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 109-125
    4. Random Variables

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 127-152
    5. Probability Distributions

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 153-178
  4. Inductive Statistics

    1. Front Matter

      Pages 179-179
    2. Inference

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 181-208
    3. Hypothesis Testing

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 209-247
    4. Linear Regression

      • Christian Heumann, Michael Schomaker, Shalabh
      Pages 249-295
  5. Back Matter

    Pages 297-456

About this book

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

  • Department of Statistics, Ludwig-Maximilians-Universität München, München, Germany

    Christian Heumann

  • Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa

    Michael Schomaker

  • Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, India

    Shalabh

About the authors

Dr. Christian Heumann is a professor at the Ludwig-Maximilian-Universität Munich, 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.

Dr. Michael Schomaker is a Senior Researcher and Biostatistician at the Centre For Infectious Disease Epidemiology & Research (CIDER), University of Cape Town, South Africa. He received his doctoral degree from the University of Munich. He has taught undergraduate students from the business and medical sciences for many years and has written contributions for various introductory textbooks. His research chiefly focuses on missing data, causal inference, model averaging and HIV/AIDS.  

Dr. 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, error-measurement models, missing data models and sampling theory.

Bibliographic Information

Buying options

eBook USD 59.99
Price excludes VAT (USA)
  • ISBN: 978-3-319-46162-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 74.99
Price excludes VAT (USA)
Hardcover Book USD 119.99
Price excludes VAT (USA)