Kutner, Nachtsheim, Neter, Wasserman, "Applied Linear Regression Models, 4/e (ALRM4e)" is the long established leading authoritative text and reference on regression (previously Neter was lead author.) For students in most any discipline where statistical analysis or interpretation is used, "ALRM" has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in any discipline. "ALRM 4e" provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor.
it's a well written book. The reprinted one is also good thought the papers are really thin. The best thing is that it still contains the original cd from the book, giving some data and answers.
评分it's a well written book. The reprinted one is also good thought the papers are really thin. The best thing is that it still contains the original cd from the book, giving some data and answers.
评分it's a well written book. The reprinted one is also good thought the papers are really thin. The best thing is that it still contains the original cd from the book, giving some data and answers.
评分it's a well written book. The reprinted one is also good thought the papers are really thin. The best thing is that it still contains the original cd from the book, giving some data and answers.
评分it's a well written book. The reprinted one is also good thought the papers are really thin. The best thing is that it still contains the original cd from the book, giving some data and answers.
很细致很细致
评分2019.09.26 现在是开学的第5周 老师快速地过完了前11章,并告诉我们期末考试有70%的内容来自前11章。看来之后得自己好好消化消化
评分好了好了考完以后本科就考完了
评分算是经典教材
评分推导还可以,证明就一般吧!不过真的说的很详细了,包括dynamic regression, penalty regression, 等等
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