{"product_id":"9781118627365","title":"Introduction to Linear Regression Analysis","description":"\u003cb\u003ePraise for the \u003ci\u003eFourth Edition\u003c\/i\u003e\u003c\/b\u003e \u003cp\u003e\"As with previous editions, the authors have produced a leading textbook on regression.\"\u003cbr\u003e —\u003ci\u003eJournal of the American Statistical Association\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA comprehensive and up-to-date introduction to\u003c\/b\u003e \u003cb\u003ethe fundamentals of regression analysis\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eIntroduction to Linear Regression Analysis, Fifth Edition\u003c\/i\u003e continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.\u003c\/p\u003e \u003cp\u003eFollowing a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The \u003ci\u003eFifth Edition\u003c\/i\u003e features numerous newly added topics, including:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models\u003c\/li\u003e \u003cli\u003eRegression models with random effects in addition to a discussion on subsampling and the importance of the mixed model\u003c\/li\u003e \u003cli\u003eTests on individual regression coefficients and subsets of coefficients\u003c\/li\u003e \u003cli\u003eExamples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eIn addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eIntroduction to Linear Regression Analysis, Fifth Edition\u003c\/i\u003e is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47134543773936,"sku":"9781118627365","price":151.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781118627365_p0.jpg?v=1763694899","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781118627365","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}