Predictive HR Analytics, Paperback/Mong Shen Ng

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Description You don't need to spend months learning Python, R, or SQL programming language, and you don't need to learn and buy expensive statistical software like SPSS or SAS. This is the only book that teaches you Predictive Analytics using Excel (which you already have) This book not only share with you the analytics findings of other companies, but also teaches you how to derive it by yourself. It covers the ARHAT Predictive HR Analytics framework, teaches you data-storytelling & data-visualization techniques, and teaches you how to use Excel's statistical tools (Decision trees, Correlation, Multiple Regression, Logistic Regression, Chi-Square) with step-by-step print-screen instructions. This is the only book that covers the full HR Analytics scope (Benefits, Compensation, Culture, Diversity & Inclusion, Engagement, Leadership, Learning & Development, Payroll, Personality Traits, Performance Management, Recruitment, Sales Incentives) with numerous real-world examples, & shows how Predictive HR Analytics with Excel can help you (1) Predict who are the people at risk of leaving using Decision tree, Correlation, Excel Logistic Regression, etc. (e. g. employee aged 30, who stays more than xx km from the company, who is rated "average for performance", has a 90% probability of resigning in her 3rd year.).(2) Identify where the best people come from and how successful a candidate will be if hired using simple correlation (E. g. Customer Service staff and Sales staff with x & y personality traits are likely to be good performers if hired).(3) Predict impact of Employee Engagement on customer satisfaction, revenue and Shareholder Returns, etc. using Excel Multiple Regression. (e. g. 1% increase in employee engagement leads to $100k increase in company revenue, 2% increase in customer satisfaction, 1% increase in Shareholders return, 1-day reduction in average sick leave, etc.).(4) Predict financial impact of training using Excel Multiple Regression (e. g. training satisfact