Authors:
- Contains examples that use real or simulated data to illustrate the methods of descriptive and inferential statistics
- Features a wealth of carefully selected real-life examples
- Presents implementations of selected examples in the language R
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 176)
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Table of contents (3 chapters)
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Front Matter
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Back Matter
About this book
This book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R.
The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.Authors and Affiliations
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Faculty of Automatic Control, Electronics and Computer Science, Silesian Technical University, Gliwice, Poland
Katarzyna Stapor
Bibliographic Information
Book Title: Introduction to Probabilistic and Statistical Methods with Examples in R
Authors: Katarzyna Stapor
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-45799-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-45798-3Published: 23 May 2020
Softcover ISBN: 978-3-030-45801-0Published: 23 May 2021
eBook ISBN: 978-3-030-45799-0Published: 22 May 2020
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: VIII, 157
Number of Illustrations: 9 b/w illustrations, 24 illustrations in colour
Topics: Applied Statistics, Data Engineering, Engineering Mathematics