Statistical Methods, Students Solutions Manual (e-only) PDF Download

Author: Rudolf J. Freund
Publisher: Academic Press
ISBN: 0123850681
Category : Mathematics
Languages : en
Pages : 69

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Book Description
Statistical Methods, Students Solutions Manual (e-only)

Author: Rudolf J. Freund
Publisher: Elsevier
ISBN: 0080498221
Category : Mathematics
Languages : en
Pages : 694

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Book Description
This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters

Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0123846684
Category :
Languages : en
Pages : 191

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Book Description

Author: Alan Agresti
Publisher: Pearson
ISBN: 9780134512792
Category : Social sciences
Languages : en
Pages : 0

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Book Description
This manual contains completely worked-out solutions for all the odd-numbered exercises in the text.

Author: Larry Wasserman
Publisher: Springer Science & Business Media
ISBN: 0387217363
Category : Mathematics
Languages : en
Pages : 446

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Book Description
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Author: G. Geoffrey Vining
Publisher:
ISBN: 9780538737234
Category : Technology & Engineering
Languages : en
Pages : 618

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Book Description
STATISTICAL METHODS FOR ENGINEERS, 3e, International Edition offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers.

Author: Christian Robert
Publisher: Springer Science & Business Media
ISBN: 1475741456
Category : Mathematics
Languages : en
Pages : 670

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Book Description
We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

Author: Robin H. Lock
Publisher: John Wiley & Sons
ISBN: 1119682169
Category : Mathematics
Languages : en
Pages : 866

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Book Description
Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.

Author: R. Lyman Ott
Publisher:
ISBN: 9781305269484
Category : Foreign Language Study
Languages : en
Pages : 256

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Book Description
Contains fully worked-out solutions to all of the odd-numbered exercises in the text, giving students a way to check their answers and ensure that they took the correct steps to arrive at an answer.

Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 0387216065
Category : Mathematics
Languages : en
Pages : 545

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Book Description
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.