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Author: ANONIMO
Publisher: Addison Wesley Publishing Company
ISBN: 9780321527592
Category : Education
Languages : en
Pages :
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Book Description
Author: ANONIMO
Publisher: Addison Wesley Publishing Company
ISBN: 9780321527592
Category : Education
Languages : en
Pages :
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Book Description
Author: Richard D. de Veaux
Publisher: Pearson
ISBN: 9780134307237
Category : Mathematics
Languages : en
Pages :
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Book Description
Author: Richard D. De Veaux
Publisher: Addison-Wesley
ISBN: 9780321514189
Category : Education
Languages : en
Pages :
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Book Description
Author: Richard De Veaux
Publisher: Pearson
ISBN: 9780135834800
Category :
Languages : en
Pages :
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Author: Richard D. De Veaux
Publisher:
ISBN: 9780134851303
Category :
Languages : en
Pages :
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Book Description
Author: Richard D. De Veaux
Publisher: Addison Wesley Longman
ISBN: 9780321692559
Category : Mathematical statistics
Languages : en
Pages : 0
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Book Description
Stats: Data and Models, Third Edition, will intrigue and challenge students by encouraging them to think statistically and by emphasizing how statistics helps us understand the world. Praised by students and instructors alike for its readability and ease of comprehension, this text focuses on statistical thinking and data analysis. The authors draw from their wealth of consulting experience to craft compelling examples, which encourages students to learn how to reason with data. This book is organized into short chapters that concentrate on one topic at a time, offering instructors maximum flexibility in planning their courses. The text is appropriate for a one-or-two semester introductory statistics course and includes advanced topics, such as Analysis of Variance (ANOVA), Multiple Regression, and Nonparametrics.
Author: Oak Ridge National Laboratory
Publisher:
ISBN:
Category : Information storage and retrieval systems
Languages : en
Pages : 296
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Book Description
Author: Norman Matloff
Publisher: CRC Press
ISBN: 1351645897
Category : Business & Economics
Languages : en
Pages : 439
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Book Description
Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at the traditional statistical regression course, presenting a contemporary treatment in line with today's applications and users. The text takes a modern look at regression: * A thorough treatment of classical linear and generalized linear models, supplemented with introductory material on machine learning methods. * Since classification is the focus of many contemporary applications, the book covers this topic in detail, especially the multiclass case. * In view of the voluminous nature of many modern datasets, there is a chapter on Big Data. * Has special Mathematical and Computational Complements sections at ends of chapters, and exercises are partitioned into Data, Math and Complements problems. * Instructors can tailor coverage for specific audiences such as majors in Statistics, Computer Science, or Economics. * More than 75 examples using real data. The book treats classical regression methods in an innovative, contemporary manner. Though some statistical learning methods are introduced, the primary methodology used is linear and generalized linear parametric models, covering both the Description and Prediction goals of regression methods. The author is just as interested in Description applications of regression, such as measuring the gender wage gap in Silicon Valley, as in forecasting tomorrow's demand for bike rentals. An entire chapter is devoted to measuring such effects, including discussion of Simpson's Paradox, multiple inference, and causation issues. Similarly, there is an entire chapter of parametric model fit, making use of both residual analysis and assessment via nonparametric analysis. Norman Matloff is a professor of computer science at the University of California, Davis, and was a founder of the Statistics Department at that institution. His current research focus is on recommender systems, and applications of regression methods to small area estimation and bias reduction in observational studies. He is on the editorial boards of the Journal of Statistical Computation and the R Journal. An award-winning teacher, he is the author of The Art of R Programming and Parallel Computation in Data Science: With Examples in R, C++ and CUDA.
Author: William Craine
Publisher: Pearson
ISBN: 9780321989970
Category : Mathematical statistics
Languages : en
Pages : 0
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Book Description
Author: Richard D. De Veaux
Publisher:
ISBN: 9780321986498
Category : DVD-ROMs
Languages : en
Pages : 0
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Book Description
Richard De Veaux, Paul Velleman, and David Bock wrote Stats: Data and Models with the goal that students and instructors have as much fun reading it as they did writing it. Maintaining a conversational, humorous, and informal writing style, this new edition engages students from the first page. The authors focus on statistical thinking throughout the text and rely on technology for calculations. As a result, students can focus on developing their conceptual understanding. Innovative Think/Show/Tell examples give students a problem-solving framework and, more importantly, a way to think throug.
