Applied Statistics in Business and Economics

Applied Statistics in Business and Economics

Author: David P. Doane

Publisher:

Published: 2006-02

Total Pages: 834

ISBN-13: 9780071108140

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David Doane offers an Excel focused approach to using statistics in business. All statistical concepts are illustrated with applied examples immediately upon introduction.


Applied Statistics in Business and Economics

Applied Statistics in Business and Economics

Author: David P. Doane

Publisher:

Published: 2015-03-16

Total Pages: 0

ISBN-13: 9781259255885

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Provides meaning to the use of statistics by using business situations and data. This book communicates the meaning of variation in a business context; uses data and business applications; and incorporates current statistical practices and offers practical advice.


Introductory Statistics for Business and Economics

Introductory Statistics for Business and Economics

Author: Thomas H. Wonnacott

Publisher:

Published: 1984-05

Total Pages: 126

ISBN-13: 9780471809883

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This Fourth Edition includes new sections on graphs, robust estimation, expected value and the bootstrap, in addition to new material on the use of computers. The regression model is well covered, including both nonlinear and multiple regression. The chapters contain many real-life examples and are relatively self-contained, making adaptable to a variety of courses.


Applied Statistics and Multivariate Data Analysis for Business and Economics

Applied Statistics and Multivariate Data Analysis for Business and Economics

Author: Thomas Cleff

Publisher: Springer

Published: 2019-07-10

Total Pages: 488

ISBN-13: 303017767X

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This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.


Statistical Techniques in Business and Economics

Statistical Techniques in Business and Economics

Author: Douglas A. Lind

Publisher: McGraw-Hill/Irwin

Published: 2002-11-01

Total Pages: 830

ISBN-13: 9780072874167

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Why make statistics harder than it has to be? Lind/Marchal/Mason: STATISTICAL TECHNIQUES IN BUSINESS AND ECONOMICS, 11/e is a perennial market best seller due to its comprehensive coverage of statistical tools and methods delivered in a student friendly, step-by-step format. The text is non-threatening and presents concepts clearly and succinctly with a conversational writing style. All statistical concepts are illustrated with solved applied examples immediately upon introduction. Modern computing tools and applications are introduced, but the text maintains a focus on presenting statistics content as oppose to technology or programming methods, and the eleventh edition continues as a ‘students’ text with increased emphasis on interpretation of data and results.lts.


Loose-Leaf for Applied Statistics in Business and Economics

Loose-Leaf for Applied Statistics in Business and Economics

Author: Lori . Seward

Publisher: McGraw-Hill Education

Published: 2021-01-12

Total Pages: 848

ISBN-13: 9781264098569

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Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how. The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics. It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets.