Description

Book Synopsis

This book provides a conceptual introduction to regression analysis and machine learning and their applications in education research. It discusses their diverse applications, including its 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 decisio

Regression and Machine Learning for Education

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    Order before 4pm tomorrow for delivery by Tue 9 Jun 2026.

    A Paperback by Cody Dingsen

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      View other formats and editions of Regression and Machine Learning for Education by Cody Dingsen

      Publisher: Taylor & Francis Ltd
      Publication Date: 1/1/2024
      ISBN13: 9781032510071, 978-1032510071
      ISBN10: 1032510072

      Description

      Book Synopsis

      This book provides a conceptual introduction to regression analysis and machine learning and their applications in education research. It discusses their diverse applications, including its 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 decisio

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