Applied Linear Regression Models Revised Edition with Student CD-ROM

Applied Linear Regression Models Revised Edition with Student CD-ROM PDF Author: Michael H Kutner, PH.D.
Publisher: McGraw-Hill Europe
ISBN: 9780071115193
Category :
Languages : en
Pages : 701

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Book Description

Applied Linear Regression Models Revised Edition with Student CD-ROM

Applied Linear Regression Models Revised Edition with Student CD-ROM PDF Author: Michael H Kutner, PH.D.
Publisher: McGraw-Hill Europe
ISBN: 9780071115193
Category :
Languages : en
Pages : 701

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Book Description


MP Applied Linear Regression Models-Revised Edition with Student CD

MP Applied Linear Regression Models-Revised Edition with Student CD PDF Author: John Neter
Publisher: McGraw-Hill Education
ISBN: 9780073014661
Category : Business & Economics
Languages : en
Pages : 701

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Book Description
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.

Interpretable Machine Learning

Interpretable Machine Learning PDF Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320

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Book Description
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Handbook of Applied Economic Statistics

Handbook of Applied Economic Statistics PDF Author: Aman Ullah
Publisher: CRC Press
ISBN: 1482269902
Category : Business & Economics
Languages : en
Pages : 646

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Book Description
This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.

Restoring Diversity

Restoring Diversity PDF Author: Donald A. Falk
Publisher:
ISBN:
Category : Nature
Languages : en
Pages : 536

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Book Description
The reintroduction of rare and endangered species to their natural habitat is one of emerging tools of ecosystem management. Yet despite hundreds of ongoing projects, the biological underpinnings of such activity are poorly understood, and important questions remain. Restoring Diversity provides biological, policy, and regulatory foundations for successful restoration of rare plants. Topics considered include the strategic and legal context for rare plant restoration, the biology of restoration, use (and misuse) of mitigation in rare plant conservation, and case studies from across the United States. Restoring Diversity presents model guidelines for the reintroduction of endangered plants - guidelines that incorporate ideas contained in the book's chapters with the wide-ranging experience of experts in the field. It is a pathbreaking work that not only unifies concepts in the field of restoration, but also fills significant technical and policy gaps and provides operational tools for successful restorations.

Student Solutions Manual for Applied Linear Regression Models

Student Solutions Manual for Applied Linear Regression Models PDF Author: Michael Kutner
Publisher: McGraw-Hill Education
ISBN: 9780072918397
Category : Education
Languages : en
Pages :

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Book Description


Introduction to Time Series and Forecasting

Introduction to Time Series and Forecasting PDF Author: Peter J. Brockwell
Publisher: Springer Science & Business Media
ISBN: 1475725264
Category : Mathematics
Languages : en
Pages : 429

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Book Description
Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Using R for Introductory Statistics

Using R for Introductory Statistics PDF Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522

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Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Introduction to GNU Octave

Introduction to GNU Octave PDF Author: Jason Lachniet
Publisher: Lulu.com
ISBN: 0359329640
Category : Education
Languages : en
Pages : 156

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Book Description
A brief introduction to scientific computing with GNU Octave. Designed as a textbook supplement for freshman and sophomore level linear algebra and calculus students.

Introduction to Computational Science

Introduction to Computational Science PDF Author: Angela B. Shiflet
Publisher: Princeton University Press
ISBN: 140085055X
Category : Computers
Languages : en
Pages : 857

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Book Description
The essential introduction to computational science—now fully updated and expanded Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects. The only introductory textbook of its kind—now fully updated and expanded Features two new chapters on agent-based simulations and modeling with matrices Increased coverage of high-performance computing and its applications Includes additional modules, review questions, exercises, and projects An online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors) An online illustration package is available to professors