Foundations of Programming, Statistics, and Machine Learning for Business Analytics

Ram D. Gopal is the Information Systems Society’s Distinguished Fellow and Alan Turing Institute’s Turing Fellow, a Professor of Information Systems and Management, and Pro-Dean for Research, Engagement, and Impact at the Warwick Business School.  Dan Philps is a veteran quantitative investment manager and a widely published artificial intelligence (AI) researcher.  Tillman Weyde is a Reader in Computer Science at City, University of London. Before joining City in 2005, he worked as a researcher in the Research Department for Music and Media Technology at the University of Osnabrück.

• Chapter 1: Introduction To Programming And StatisticsChapter 2: Summarizing And Visualizing DataChapter 3: Summarizing And Visualizing DataChapter 4: Programming FundamentalsChapter 5: Programming FundamentalsChapter 6: DistributionsChapter 7: Statistical Testing – Concepts and StrategyChapter 8: Statistical Testing – Concepts and StrategyChapter 9: Nonparametric TestsChapter 10: Reality CheckChapter 11: Fundamentals of EstimationChapter 12: Linear ModelsChapter 13: General Linear ModelsChapter 14: Regression Diagnostics And StructureChapter 15: Timeseries And ForecastingChapter 16: Introduction To Machine LearningChapter 17: Model Selection And Cross ValidationChapter 18: Regression Models In Machine LearningChapter 19: Classification Models And EvaluationChapter 20: Automated Machine Learning