Confidently use predictive analytic and statistical techniques to identify key relationships and trends in HR-related data to aid strategic organizational decision-making.
Confidently use predictive analytic and statistical techniques to identify key relationships and trends in HR-related data to aid strategic organizational decision-making.
Martin R Edwards is a Professor in Management at UQ Business School, University Queensland, Australia and has been teaching HR and Statistics for over 20 years. Kirsten Edwards is the Global Head of People Data and Analytics at Rio Tinto. With over two decades of international experience in Analytics, HR and Management Consulting, she has supported various organisations across multiple sectors, empowering them to utilise people data and analytics more effectively. Daisung Jang Daisung Jang is an Assistant Professor at Melbourne Business School. He has over a decade of experience in data visualization and analysis using R. He has conducted workshops for PhD students and academic staff on statistical analyses using R.
Inhaltsangabe
Chapter 01: Understanding HR analytics; Chapter 02: HR information systems and data; Chapter 03: Analysis strategies; Chapter 04: Case study 1 Diversity analytics; Chapter 05: Case study 2 Employee attitude surveys engagement and workforce perceptions; Chapter 06: Case study 3 Predicting employee turnover; Chapter 07: Case study 4 Predicting employee performance; Chapter 08: Case study 5 Recruitment and selection analytics; Chapter 09: Case study 6 Monitoring the impact of interventions; Chapter 10: Business applications Scenario modelling and business cases; Chapter 11: More advanced HR analytic techniques; Chapter 12: Reflection on HR analytics Usage, ethics and limitations; Chapter 13: Appendix
Chapter 01: Understanding HR analytics; Chapter 02: HR information systems and data; Chapter 03: Analysis strategies; Chapter 04: Case study 1 Diversity analytics; Chapter 05: Case study 2 Employee attitude surveys engagement and workforce perceptions; Chapter 06: Case study 3 Predicting employee turnover; Chapter 07: Case study 4 Predicting employee performance; Chapter 08: Case study 5 Recruitment and selection analytics; Chapter 09: Case study 6 Monitoring the impact of interventions; Chapter 10: Business applications Scenario modelling and business cases; Chapter 11: More advanced HR analytic techniques; Chapter 12: Reflection on HR analytics Usage, ethics and limitations; Chapter 13: Appendix
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