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Regression And Machine Learning For Education Sciences Using R Cody Dingsen

  • SKU: BELL-60220198
Regression And Machine Learning For Education Sciences Using R Cody Dingsen
$ 31.00 $ 45.00 (-31%)

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Regression And Machine Learning For Education Sciences Using R Cody Dingsen instant download after payment.

Publisher: Routledge
File Extension: PDF
File size: 30.87 MB
Author: Cody Dingsen
ISBN: 9781040145043, 1040145043
Language: English
Year: 2024

Product desciption

Regression And Machine Learning For Education Sciences Using R Cody Dingsen by Cody Dingsen 9781040145043, 1040145043 instant download after payment.

This book provides a conceptual introduction to regression analysis and machine learning and their applications in education research. It discusses their diverse applications, including their role in predicting future events based on the current, data or explaining why some phenomena occur. These identified important predictors provide data-based evidence for educational and psychological decision-making. Offering an applications-oriented approach while mapping out fundamental methodological developments, this book lays a sound foundation for understanding essential regression and machine learning concepts for data analytics. The first
part of the book discusses regression analysis and provides a sturdy foundation to understand the logic of machine learning. With each chapter, the discussion and development of each statistical concept and data analytical technique is presented from an applied perspective, with the statistical results providing insights into decisions and solutions to problems using R. Based on practical examples, and written in a concise and accessible style, the book is learner-centric and does a remarkable job in breaking down complex concepts. Regression and Machine Learning for Education Sciences Using R is primarily for students or practitioners in education and psychology, although individuals from other related disciplines can also find the book beneficial. The dataset and examples used in the book are from an educational setting, and students will find that this text provides a good preparation ground for studying more statistical and data analytical materials.

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