Introduction to probabilistic and statistical methods with examples in R
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…
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- Full title :Introduction to probabilistic and statistical methods with examples in R / Katarzyna Stapor.
Summary
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.
Read More ↓Edition Statements
- Publication Date:2020.
Publication Statements
- Publisher(s):Springer
- Place of Publication:Cham
- Language:eng
- Publication Date:2020.
The Physical Object
- Description:1 online resource (163 pages)
Edition Identifiers
- ISBN:9783030457990, 3030457990
- DOI:10.1007/978-3-030-45799-0
- oclc:on1156130853
- LC Classification:QA276
- Dewey Decimal:519.5
Table of Contents
Elements of Probability Theory -- Descriptive and Inferential Statistics -- Linear Regression and Correlation.
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