Fundamentals of Predictive Analytics with JMP, Third Edition

Written for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded third edition of Fundamentals of Predictive Analytics with JMP bridges the gap between courses on basic statistics, which focus on univariate and bivariate analysis, and courses on data mining and predictive analytics. Going beyond the theoretical foundation, this book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. Using JMP 17, this book discusses the following new and enhanced features in an example-driven format:an add-in for Microsoft Excel Graph Builderdirty datavisualizationregressionANOVAlogistic regressionprincipal component analysisLASSOelastic netcluster analysisdecision treesk-nearest neighborsneural networksbootstrap forestsboosted treestext miningassociation rules model comparisontime series forecastingWith a new, expansive chapter on time series forecasting and more exercises to test your skills, this third edition is invaluable to those who need to expand their knowledge of statistics and apply real-world, problem-solving analysis.