1. Introduction -- 2. Basic Statistics and Functions using R -- 3. Regression Fundamentals -- 4. Simple Linear Regression -- 5. Multiple Regression -- 6. Estimation Intervals and Analysis of Variance -- 7. Predictor Variable Transformations -- 8. Model Diagnostics -- 9. Variable Selection.

Foreword by Prof. John L. Hennessy (Stanford University, California, USA) and Prof. David A. Patterson (University of California at Berkeley, USA). - Preface . - Introduction. - PART I - An Infl ection Point for Enterprise Applications . - 1 Desirability, Feasibility, Viability - The Impact of...

Chapter 1: Urgency in Healthcare Data Analytics -- Chapter 2: Analytics and Knowledge Management in Healthcare -- Chapter 3: Visualization -- Chapter 4: Association Rules -- Chapter 5: Cluster Analysis -- Chapter 6: Time Series Forecasting -- Chapter 7: Classification Models -- Chapter 8:...

Chapter 1: Introduction -- Chapter 2: Data for Analytics in Small Businesses -- Chapter 3: Business Analytics Consulting -- Chapter 4: Business Analytics Consulting Phases -- Chapter 5: Descriptive Analytics Tools -- Chapter 6: Predicting Numeric Outcomes -- Chapter 7: Classification Techniques...