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Introduction to Probabilistic and Statistical Methods with Examples in R / / Katarzyna Stapor

By: Stapor, Katarzyna, autor
Contributor(s): SpringerLink (Online service)
Material type: materialTypeLabelE-bookSeries: (Intelligent Systems Reference Library, 1868-4394; 176); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: First edition.Description: 1 recurso en línea (VIII, 157 páginas) : 33 ilustraciones, 24 ilustraciones a color.ISBN: 9783030457990.Subject: Estadística matemática | R (Lenguaje de programación)Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Elements of Probability Theory -- Descriptive and Inferential Statistics -- Linear Regression and Correlation.
Abstract: 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. .
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA276 2020 EB (Browse shelf(Opens below)) Acceso electrónico eBook.24062117
Total holds: 0

Elements of Probability Theory -- Descriptive and Inferential Statistics -- Linear Regression and Correlation.

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. .

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