Original PDF Ebook – Applied Regression Modeling3rd Edition – 9781119615866

Original PDF Ebook – Applied Regression Modeling3rd Edition – 9781119615866

Master the fundamentals of regression without learning calculus with this one-stop resource_x000D_
The newly and thoroughly revised 3rd Edition of Applied Regression Modeling delivers a concise but comprehensive treatment of the application of statistical regression analysis for those with little or no background in calculus. Accomplished instructor and author Dr. Iain Pardoe has reworked many of the more challenging topics, included learning outcomes and additional end-of-chapter exercises, and added coverage of several brand-new topics including multiple linear regression using matrices._x000D_
The methods described in the text are clearly illustrated with multi-format datasets available on the book’s supplementary website. In addition to a fulsome explanation of foundational regression techniques, the book introduces modeling extensions that illustrate advanced regression strategies, including model building, logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series forecasting. Illustrations, graphs, and computer software output appear throughout the book to assist readers in understanding and retaining the more complex content. Applied Regression Modeling covers a wide variety of topics, like:_x000D_
Simple linear regression models, including the least squares criterion, how to evaluate model fit, and estimation/prediction_x000D_
Multiple linear regression, including testing regression parameters, checking model assumptions graphically, and testing model assumptions numerically_x000D_
Regression model building, including predictor and response variable transformations, qualitative predictors, and regression pitfalls_x000D_
Three fully described case studies, including one each on home prices, vehicle fuel efficiency, and pharmaceutical patches_x000D_
Perfect for students of any undergraduate statistics course in which regression analysis is a main focus, Applied Regression Modeling also belongs on the bookshelves of non-statistics graduate students, including MBAs, and for students of vocational, professional, and applied courses like data science and machine learning.