{"product_id":"applied-regression-modeling-hardcover","title":"Applied Regression Modeling - Hardcover","description":"\u003cp\u003eby \u003cb\u003eIain Pardoe\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eMaster the fundamentals of regression without learning calculus with this one-stop resource\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe newly and thoroughly revised 3rd Edition of \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eThe 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. \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e covers a wide variety of topics, like: \u003c\/p\u003e \u003cul\u003e \u003cli\u003eSimple linear regression models, including the least squares criterion, how to evaluate model fit, and estimation\/prediction\u003c\/li\u003e \u003cli\u003eMultiple linear regression, including testing regression parameters, checking model assumptions graphically, and testing model assumptions numerically\u003c\/li\u003e \u003cli\u003eRegression model building, including predictor and response variable transformations, qualitative predictors, and regression pitfalls\u003c\/li\u003e \u003cli\u003eThree fully described case studies, including one each on home prices, vehicle fuel efficiency, and pharmaceutical patches\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for students of any undergraduate statistics course in which regression analysis is a main focus, \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e 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.\u003c\/p\u003e\u003ch3\u003eFront Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eMaster the fundamentals of regression without learning calculus with this one-stop resource\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eThe newly and thoroughly revised 3rd Edition of \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e 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. \u003c\/p\u003e\u003cp\u003eThe 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. \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e covers a wide variety of topics, like: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eSimple linear regression models, including the least squares criterion, how to evaluate model fit, and estimation\/prediction\u003c\/li\u003e \u003cli\u003eMultiple linear regression, including testing regression parameters, checking model assumptions graphically, and testing model assumptions numerically\u003c\/li\u003e \u003cli\u003eRegression model building, including predictor and response variable transformations, qualitative predictors, and regression pitfalls\u003c\/li\u003e \u003cli\u003eThree fully described case studies, including one each on home prices, vehicle fuel efficiency, and pharmaceutical patches\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for students of any undergraduate statistics course in which regression analysis is a main focus, \u003ci\u003eApplied Regression Modeling\u003c\/i\u003e 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.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eIain Pardoe, PhD, \u003c\/b\u003e received his PhD in Statistics from the University of Minnesota. He\u003cb\u003e\u003c\/b\u003e is an Online Instructor of the \"Regression Methods\" graduate course at Pennsylvania State University. He also teaches \"Biostatistics,\" \"Mathematics for Computing Science,\" and \"Mathematics for Teachers\" at Thompson Rivers University and was previously an Associate Professor at the University of Oregon.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 336\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.75 x 10 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e December 03, 2020\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42729360851007,"sku":"9781119615866","price":229.74,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0105\/8226\/1823\/files\/3e134430a3cc5ef2c326873ecbdfaa6a.webp?v=1765121912","url":"https:\/\/dhlswag.com\/products\/applied-regression-modeling-hardcover","provider":"BBB","version":"1.0","type":"link"}