Ord/Fildes PRINCIPLES OF BUSINESS FORECASTING, 1E gives users the tools and insight to make the most effective forecasts drawing on the latest research ideas. Ord and Fildes have designed PRINCIPLES OF BUSINESS FORECASTING for users who have taken a first course in applied statistics or who have an equivalent background. Whether used by students or current practitioners, this book provides an introduction to both standard and advanced forecasting methods and their underlying models, and also includes general principles to guide and simplify forecasting practice. A key strength of the book is its emphasis on real data sets, taken from government and business sources and used in each chapter's examples. Forecasting techniques are demonstrated using a variety of software platforms and the companion website provides easy-to-use Excel macros to support the basic methods. After the introductory chapters, the focus shifts to using extrapolative methods (exponential smoothing and ARIMA) and then to statistical model-building using multiple regression. In later chapters, the authors cover more novel techniques such as data mining and judgmental methods, and also examine organizational issues of implementation and the development of a forecasting support system within an organization.

Principles of Business Forecasting

Business & Money

Ord, Keith

Fildes, Robert

Management & Leadership

Cengage Learning'

This set offers the complete, classic Kendall's Advanced Theory of Statistics in a single value-for-money pack. The latest set includes the brand new second edition of the popular "Volume 2B: Bayesian Inference," along with the sixth editions of "Volume I: Distribution Theory," and "Volume 2A: Classical Inference and the Linear Model."

Kendall's Advanced Theory of Statistics

Science & Math

Arnold, Steven

O'Hagan, Anthony

Stuart, the late Alan

Forster, Jon

Mathematics

Hodder Education Publishers

A comprehensive reference for modern statistical distributions and related sample theory. Substantially revised, this edition contains an extensive discussion of the bivariate and multivariate versions of the standard distributions and families. Includes new material on skewness and kurtosis, hazard rate distributions, the bootstrap, evaluation of multivariate normal integral and ratios of quadratic forms. Features over 200 additional references, 40 new exercises plus 20 further examples.

Kendall's Advanced Theory of Statistics, Distribution Theory (Volume 1)

Stuart, Alan

Oxford University Press, New York

Kendall's Advanced Theory of Statistics and Kendall's Library of Statistics The development of modern statistical theory is reflected in the history of the late Sir Maurice Kenfall's volumes, The Advanced Theory of Statistics. This landmark publication began life as a two-volume work and grew steadily as a single-authored work until the 1950s. In this edition, there is new material on skewness and kurtosis, hazard rate distribution, the bootstrap, the evaluation of the multivariate normal integral and ratios of quadratic forms. It also includes over 200 new references, 40 new exercises, and 20 further examples in the main text.

Kendall's Advanced Theory of Statistics, Distribution Theory

wiley

The development of statistical theory in the past fifty years is faithfully reflected in the history of the late Sir Maurice Kendall’s volumes The Advanced Theory of Statistics. The Advanced Theory began life as a two volume work (Volume 1, 1943; Volume 2, 1946) and grew steadily, as a single authored work until the late fifties. At that point Alan Stuart became involved and the Advanced Theory was rewritten in three volumes. When Keith Ord joined in the early eighties, Volume 3 became the largest and plans were developed to expand it into a series of monographs called the Kendall's Library of Statistics which would devote a book to each of the modern developments in statistics. This series is well on the way with 5 titles in print and a further 7 on the way. A new volume on Bayesian Inference was also commissioned from Tony O'Hagan and published in 1994 as Volume 2B of the Advanced Theory. This Volume 2A is therefore the completely updated Volume 2 - Classical Inference and Relationship. A new author, Steven Arnold, was invited to join Keith Ord and they have between them produced a work of the highest quality. References have been updated and material revised throughout. A new chapter on the linear model and least squares estimation has been added.

Kendall's Advanced Theory of Statistics, Classical Inference and the Linear Model

Principles of Business Forecasting--2nd ed

This second edition of Principles of Business Forecasting by Keith Ord, Robert Fildes, and newest author Nikolaos Kourentzes serves as both a textbook for students and as a reference book for experienced forecasters in a variety of fields. The authors' motivation for writing this book, is to give users the tools and insight to make the most effective forecasts drawing on the latest research ideas, without being overly technical. The book is unique in its design, providing an introduction to both standard and advanced forecasting methods, as well as a focus on general principles to guide and simplify forecasting practice for those with little or no professional experience. One of the book’s key strengths is the emphasis on real data sets, which have been updated in this second edition. These data sets are taken from government and business sources and are used throughout in the chapter examples and exercises. Forecasting techniques are demonstrated using a variety of software platforms beyond just “R”, and a companion website provides easy-to-use Excel® macros that users can access to conduct analyses. Another important innovation in the second edition is the tutorial support for using open-source R programs, making all the methods available for use both in courses and practice.
After the introductory chapters, the focus shifts to using extrapolative methods (exponential smoothing and ARIMA), then to statistical model-building using multiple regression. The authors also cover more novel techniques including data mining and judgmental methods, which are gaining increasing attention in applications. The second edition also offers expanded material on data analytics, in particular neural nets together with software, and applications that include new research findings relevant and immediately applicable to operations, such as hierarchical modeling and temporal aggregation. Finally, the authors examine organizational issues of implementation and the development of a forecasting support system within an organization; relevant to every manager, or future manager, who must make plans or decisions based on forecasts.
Please take a moment to review the companion website for additional content in the Appendices (Basic Statistical Concepts, overview of Forecasting Software, and Forecasting in R: Tutorial and Examples) the many data sets referenced in the chapters, macros such as the Exponential Smoothing and Trend Curve Marcos and Time Series Neural Network Analysis and student study materials.

Kourentzes, Nikos

wessex, inc.

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