Introduction to Probabilistic and Statistical Methods with Examples in R
Language: English
Published by Springer, 2020
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 132.87
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - 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.
Seller Inventory # 9783030457983
- Title
- Introduction to Probabilistic and Statistical Methods with Examples in R
- Author
- Katarzyna Stapor
- Publisher
- Springer
- Publication year
- 2020
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3030457982
- ISBN 13
- 9783030457983
- Item weight
- 424 grams
- Dimensions
- 241x160x15 mm
- Series
- Book 1 of 1: Intelligent Systems Reference Library
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."Synopsis" may belong to another edition of this title.
From the Back Cover
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."About the title" may belong to another edition of this title.
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