9781118948897 - predictive analytics: parametric models for regression and classification using r di tamhane, ajit c. (18 risultati)
Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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hardcover. Condizione: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Lingua: Inglese
Editore: John Wiley & Sons Inc, New York, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Hardcover. Condizione: new. Hardcover. Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive analytics and statistical learning This book covers a broad range of topics in parametric regression and classification including multiple regression,…logistic regression (binary and multinomial), discriminant analysis, Bayesian classification, generalized linear models and Cox regression for survival data. The book also gives brief introductions to some modern computer-intensive methods such as classification and regression trees (CART), neural networks and support vector machines. The book is organized so that it can be used by both advanced undergraduate or masters students with applied interests and by doctoral students who also want to learn the underlying theory. This is done by devoting the main body of the text of each chapter with basic statistical methodology illustrated by real data examples. Derivations, proofs and extensions are relegated to the Technical Notes section of each chapter, Exercises are also divided into theoretical and applied. Answers to selected exercises are provided. A solution manual is available to instructors who adopt the text. Data sets of moderate to large sizes are used in examples and exercises. They come from a variety of disciplines including business (finance, marketing and sales), economics, education, engineering and sciences (biological, health, physical and social). All data sets are available at the books web site. Open source software R is used for all data analyses. R codes and outputs are provided for most examples. R codes are also available at the books web site. Predictive Analytics: Parametric Models for Regression and Classification Using R is ideal for a one-semester upper-level undergraduate and/or beginning level graduate course in regression for students in business, economics, finance, marketing, engineering, and computer science. It is also an excellent resource for practitioners in these fields. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
- Rilegato
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Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Lingua: Inglese
Editore: Wiley, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
- Rilegato
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Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Condizione: New. In English.
Lingua: Inglese
Editore: John Wiley & Sons Inc, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: John Wiley & Sons, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Condizione: New.
Lingua: Inglese
Editore: John Wiley & Sons Inc, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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- Prima edizione
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condizione: New. 2020. 1st Edition. hardcover. . . . . .
Lingua: Inglese
Editore: John Wiley & Sons Inc, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Hardcover. Condizione: Brand New. har/psc edition. 359 pages. 10.50x7.50x1.00 inches. In Stock.
Lingua: Inglese
Editore: John Wiley & Sons, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Condizione: New. Ajit C. Tamhane, PhD, is Professor of Industrial Engineering & Management Sciences with a courtesy appointment in Statistics at Northwestern University. He is a fellow of the American Statistical Association, Institute of Mathematical Statistics, American A.
Lingua: Inglese
Editore: John Wiley & Sons, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New.
Lingua: Inglese
Editore: John Wiley & Sons Inc, New York, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
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Hardcover. Condizione: new. Hardcover. Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive analytics and statistical learning This book covers a broad range of topics in parametric regression and classification including multiple regression,…logistic regression (binary and multinomial), discriminant analysis, Bayesian classification, generalized linear models and Cox regression for survival data. The book also gives brief introductions to some modern computer-intensive methods such as classification and regression trees (CART), neural networks and support vector machines. The book is organized so that it can be used by both advanced undergraduate or masters students with applied interests and by doctoral students who also want to learn the underlying theory. This is done by devoting the main body of the text of each chapter with basic statistical methodology illustrated by real data examples. Derivations, proofs and extensions are relegated to the Technical Notes section of each chapter, Exercises are also divided into theoretical and applied. Answers to selected exercises are provided. A solution manual is available to instructors who adopt the text. Data sets of moderate to large sizes are used in examples and exercises. They come from a variety of disciplines including business (finance, marketing and sales), economics, education, engineering and sciences (biological, health, physical and social). All data sets are available at the books web site. Open source software R is used for all data analyses. R codes and outputs are provided for most examples. R codes are also available at the books web site. Predictive Analytics: Parametric Models for Regression and Classification Using R is ideal for a one-semester upper-level undergraduate and/or beginning level graduate course in regression for students in business, economics, finance, marketing, engineering, and computer science. It is also an excellent resource for practitioners in these fields. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Lingua: Inglese
Editore: John Wiley & Sons Inc, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
- Rilegato
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Condizione: New. 2020. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: John Wiley & Sons Inc, New York, 2020
Serie: Libro 315 di 358 - Wiley Series in Probability and Statistics
- Rilegato
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Hardcover. Condizione: new. Hardcover. Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive analytics and statistical learning This book covers a broad range of topics in parametric regression and classification including multiple regression,…logistic regression (binary and multinomial), discriminant analysis, Bayesian classification, generalized linear models and Cox regression for survival data. The book also gives brief introductions to some modern computer-intensive methods such as classification and regression trees (CART), neural networks and support vector machines. The book is organized so that it can be used by both advanced undergraduate or masters students with applied interests and by doctoral students who also want to learn the underlying theory. This is done by devoting the main body of the text of each chapter with basic statistical methodology illustrated by real data examples. Derivations, proofs and extensions are relegated to the Technical Notes section of each chapter, Exercises are also divided into theoretical and applied. Answers to selected exercises are provided. A solution manual is available to instructors who adopt the text. Data sets of moderate to large sizes are used in examples and exercises. They come from a variety of disciplines including business (finance, marketing and sales), economics, education, engineering and sciences (biological, health, physical and social). All data sets are available at the books web site. Open source software R is used for all data analyses. R codes and outputs are provided for most examples. R codes are also available at the books web site. Predictive Analytics: Parametric Models for Regression and Classification Using R is ideal for a one-semester upper-level undergraduate and/or beginning level graduate course in regression for students in business, economics, finance, marketing, engineering, and computer science. It is also an excellent resource for practitioners in these fields. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
