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Introduction to statistics and data analysis : with exercises, solutions and applications in R / Christian Heumann and Michael Schomaker Shalabh.

By: Contributor(s): Material type: TextTextPublication details: Switzerland : Springer, 2016.Description: xiii, 456 pages : illustrations ; 24 cmISBN:
  • 9783319461601
Subject(s): DDC classification:
  • 000SA.01 23 H593
Contents:
Part I Descriptive Statistics: 1. Introduction and Framework.- 2. Frequency Measures and Graphical Representation of Data.- 3. Measures of Central Tendency and Dispersion.- 4. Association of Two Variables.- Part II Probability Calculus: 5. Combinatorics.- 6. Elements of Probability Theory.- 7. Random Variables.- 8. Probability Distributions.- Part III Inductive Statistics: 9. Inference.- 10. Hypothesis Testing.- 11. Linear Regression.- Appendices.
Summary: 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.
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Includes bibliographical references and index.

Part I Descriptive Statistics:
1. Introduction and Framework.-
2. Frequency Measures and Graphical Representation of Data.- 3. Measures of Central Tendency and Dispersion.-
4. Association of Two Variables.-
Part II Probability Calculus:
5. Combinatorics.-
6. Elements of Probability Theory.-
7. Random Variables.-
8. Probability Distributions.-
Part III Inductive Statistics:
9. Inference.-
10. Hypothesis Testing.-
11. Linear Regression.-
Appendices.

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.

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