Introduction to Probabilistic and Statistical Methods with Examples in R

✍ Scribed by Katarzyna Stapor

Publisher: Springer International Publishing;Springer
Year: 2020
Tongue: English
Leaves: 163
Series: Intelligent Systems Reference Library 176
Edition: 1st ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-viii
Elements of Probability Theory (Katarzyna Stapor)....Pages 1-61
Descriptive and Inferential Statistics (Katarzyna Stapor)....Pages 63-131
Linear Regression and Correlation (Katarzyna Stapor)....Pages 133-149
Back Matter ....Pages 151-157

✦ Subjects

Statistics; Applied Statistics; Engineering Mathematics

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