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Introduction to statistics and data analysis: with exercises, solutions and applications in R

Introduction to statistics and data analysis: with exercises, solutions and applications in R

Heumann, Christian, 1962- author; Schomaker, Michael, author; Shalabh, author

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

Hardback, Book. English.
Published Cham, Switzerland: Springer, [2016]
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Available at Mary Seacole Library.

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Details

Statement of responsibility: Christian Heumann, Michael Schomaker, Shalabh
ISBN: 3319461605, 9783319461601
Note: Includes bibliographical references and index.
Physical Description: xiii, 456 pages : illustrations (black and white) ; 24 cm
Subject: R (Computer program language); Mathematical statistics.

Contents

  1. Part I Descriptive Statistics: Introduction and Framework
  2. Frequency Measures and Graphical Representation of Data
  3. Measures of Central Tendency and Dispersion
  4. Association of Two Variables
  5. Part I Probability Calculus: Combinatorics
  6. Elements of Probability Theory
  7. Random Variables
  8. Probability Distributions
  9. Part III Inductive Statistics: Inference
  10. Hypothesis Testing
  11. Linear Regression
  12. Part IV Appendices: Introduction to R
  13. Solutions to Exercises
  14. Technical Appendix
  15. Visual Summaries.