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Foundations of data analysis

Record Type:	Electronic resources : Monograph/item
Title/Author:	Foundations of data analysis by Mike Nguyen.
Author:	Nguyen, Mike.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xi, 287 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Mathematical statistics.
Online resource:	https://doi.org/10.1007/978-3-032-01858-8
ISBN:	9783032018588$q(electronic bk.)

Foundations of data analysis
Nguyen, Mike.

Foundations of data analysis [electronic resource] /by Mike Nguyen. - Cham :Springer Nature Switzerland :2025. - xi, 287 p. :ill., digital ;24 cm.

1 Introduction -- 2 Prerequisites -- 3 Descriptive Statistics -- 4 Basic Statistical Inference.

This volume is designed not only as a foundation for mastering modern data analysis but also as a trusted companion for revision and review. Whether you're encountering these ideas for the first time or revisiting them to reinforce your understanding, this book provides a clear and structured pathway. It introduces essential topics such as descriptive statistics, probability, and statistical inference, while laying the groundwork for more advanced analytical methods. Emphasis is placed on conceptual clarity, interpretation, and practical intuition-making the material both rigorous and accessible. Rich with examples from business, economics, and policy research, this book equips students, professionals, and self-learners alike with the tools needed for applied data analysis and future modeling work.

ISBN: 9783032018588$q(electronic bk.)

Standard No.: 10.1007/978-3-032-01858-8doiSubjects--Topical Terms:

181877
Mathematical statistics.

LC Class. No.: QA276 / .N48 2025

Dewey Class. No.: 519.5

Foundations of data analysis
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505 0 $a 1 Introduction -- 2 Prerequisites -- 3 Descriptive Statistics -- 4 Basic Statistical Inference.
520 $a This volume is designed not only as a foundation for mastering modern data analysis but also as a trusted companion for revision and review. Whether you're encountering these ideas for the first time or revisiting them to reinforce your understanding, this book provides a clear and structured pathway. It introduces essential topics such as descriptive statistics, probability, and statistical inference, while laying the groundwork for more advanced analytical methods. Emphasis is placed on conceptual clarity, interpretation, and practical intuition-making the material both rigorous and accessible. Rich with examples from business, economics, and policy research, this book equips students, professionals, and self-learners alike with the tools needed for applied data analysis and future modeling work.
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