{"product_id":"generalized-linear-models-with-examples-in-r-von-gordon-k-smyth-peter-k-dunn","title":"Generalized Linear Models With Examples in R","description":"\n                                \n                \u003cp\u003eThis textbook presents an introduction to  generalized linear models, complete with real-world data sets and  practice problems, making it applicable for both beginning and advanced  students of applied statistics. Generalized linear models (GLMs) are  powerful tools in applied statistics that extend the ideas of multiple  linear regression and analysis of variance to include response variables  that are not normally distributed. As such, GLMs can model a wide  variety of data types including counts, proportions, and binary outcomes  or positive quantities.\u003c\/p\u003e\n                                \n                \u003cp\u003e\n                                        \n                    \u003cbr\u003e\n                                    \n                \u003c\/p\u003e\n                                The book is designed with the student in mind, making it suitable for self-study or a structured course. Beginning with an introduction to linear regression, the book also devotes time to advanced topics not typically included in introductory textbooks. It features chapter introductions and summaries, clear examples, and many practice problems, all carefully designed to balance theory and practice. The text also provides a working knowledge of applied statistical practice through the extensive use of R, which is integrated into the text. \n                \n                \u003cp\u003e\u003c\/p\u003e\n                                \n                \u003cp\u003e\n                                        \n                    \u003cbr\u003e\n                                    \n                \u003c\/p\u003e\n                                \n                \u003cp\u003eOther features include: \u003c\/p\u003e\n                                \n                \u003cp\u003e•             Advanced topics such as power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, small-dispersion asymptotics, and randomized quantile residuals \u003c\/p\u003e\n                                \n                \u003cp\u003e•             Nearly 100 data sets in the companion R package GLMsData\u003c\/p\u003e\n                                \n                \u003cp\u003e \u003c\/p\u003e\n                                \n                \u003cp\u003e•             Examples that are cross-referenced to the companion data set, allowing readers to load the data and follow the analysis in their own R session\u003c\/p\u003e\n                                   \n            \n            \u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9781441901170\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Hardcover - 9781441901170","offer_id":32962579136605,"sku":"9781441901170","price":117.69,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/6d4a15ab-b099-460f-9a6d-fe3c2568fbe4.jpg?v=1772169096","url":"https:\/\/shop.autorenwelt.de\/products\/generalized-linear-models-with-examples-in-r-von-gordon-k-smyth-peter-k-dunn","provider":"Autorenwelt Shop","version":"1.0","type":"link"}