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Predictive Analytics in Human Resource Management

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Hardback
216 Pages
4 December 2020
RRP: $395.00
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This volume is a step-by-step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organisational impact, to aid in strategising and better decision-making.

The book:

  • Presents key concepts and expands on the need and role of HR analytics in business management.
  • Utilises popular analytical tools like artificial neural networks (ANNs) and K-nearest neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening.
  • Discusses real-world corporate examples and employee data collected first-hand by the authors.
  • Includes individual chapter exercises and case studies for students and teachers.

Comprehensive and accessible, this guide will be useful for students, teachers, and researchers of data analytics, Big Data, human resource management, statistics, and economics. It will also be of interest to readers interested in learning more about statistics or programming.

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    Product Details
    ISBN-13
    9780367903213
    Author
    Shivinder Nijjer
    Publisher
    Taylor & Francis
    Published
    4 December 2020
    Format
    Hardback
    Pages
    216

    This product hasn't received any reviews yet. Be the first to review this product!

    RRP: $395.00
    $390.00
    Ships in 2-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Predictive Analytics in Human Resource Management

    RRP: $395.00
    $390.00

    Description

    This volume is a step-by-step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organisational impact, to aid in strategising and better decision-making.

    The book:

    • Presents key concepts and expands on the need and role of HR analytics in business management.
    • Utilises popular analytical tools like artificial neural networks (ANNs) and K-nearest neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening.
    • Discusses real-world corporate examples and employee data collected first-hand by the authors.
    • Includes individual chapter exercises and case studies for students and teachers.

    Comprehensive and accessible, this guide will be useful for students, teachers, and researchers of data analytics, Big Data, human resource management, statistics, and economics. It will also be of interest to readers interested in learning more about statistics or programming.

    You Can Find This Title In

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