Applied Regression Analysis For Business
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Applied Regression Analysis For Business
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Author : Jacek Welc
language : en
Publisher: Springer
Release Date : 2017-12-29
Applied Regression Analysis For Business written by Jacek Welc and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-29 with Business & Economics categories.
This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.
Applied Regression Analysis For Business And Economics
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Author : Terry E. Dielman
language : en
Publisher:
Release Date : 1991
Applied Regression Analysis For Business And Economics written by Terry E. Dielman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Commercial statistics categories.
This book is designed for short courses in regression analysis. The goal of the text is to present regression techniques in a way that avoids unnecessary mathematical rigor. The emphasis is on understanding the assumptions, knowing when and how regression might be useful in a business setting, and understanding computer output from commonly encountered statistical packages. The text utilizes the statistical packages of SAS and MINITAB. Other statistical packages containing regression procedures could also be used with little effort.
Applied Regression Analysis For Business And Economics
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Author : Terry E. Dielman
language : en
Publisher:
Release Date : 2000-09
Applied Regression Analysis For Business And Economics written by Terry E. Dielman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-09 with categories.
Applied Regression Analysis
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Author : Terry E. Dielman
language : en
Publisher:
Release Date : 2005
Applied Regression Analysis written by Terry E. Dielman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Regression analysis categories.
Applied Regression Analysis For Business And Economics
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Author : Terry E. Dielman
language : en
Publisher: South Western Educational Publishing
Release Date : 1996
Applied Regression Analysis For Business And Economics written by Terry E. Dielman and has been published by South Western Educational Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.
Disk includes: Data sets for the exercises in the text, formatted in ASCII, MINITAB, SAS, Microsoft Excel, and STATA form and accessible to any statistical software package.
Applied Regression Modeling
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Author : Iain Pardoe
language : en
Publisher: John Wiley & Sons
Release Date : 2013-01-07
Applied Regression Modeling written by Iain Pardoe and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-07 with Mathematics categories.
Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
Applied Regression Analysis For Business Economics
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Author : Dielman
language : en
Publisher: Arden Shakespeare
Release Date : 1990-09-01
Applied Regression Analysis For Business Economics written by Dielman and has been published by Arden Shakespeare this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-09-01 with categories.
Applied Regression Analysis
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Author : Christer Thrane
language : en
Publisher: Routledge
Release Date : 2019-10-16
Applied Regression Analysis written by Christer Thrane and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-16 with Business & Economics categories.
This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and perform it to perfection. This non-technical point of departure is complemented by practical examples of real-life data analysis using statistics software such as Stata, R and SPSS. Parts 1 and 2 of the book cover the basics, such as simple linear regression, multiple linear regression, how to interpret the output from statistics programs, significance testing and the key regression assumptions. Part 3 deals with how to practically handle violations of the classical linear regression assumptions, regression modeling for categorical y-variables and instrumental variable (IV) regression. Part 4 puts the various purposes of, or motivations for, regression into the wider context of writing a scholarly report and points to some extensions to related statistical techniques. This book is written primarily for those who need to do regression analysis in practice, and not only to understand how this method works in theory. The book’s accessible approach is recommended for students from across the social sciences.
Applied Linear Regression For Business Analytics With R
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Author : Daniel P. McGibney
language : en
Publisher: Springer Nature
Release Date : 2023-07-04
Applied Linear Regression For Business Analytics With R written by Daniel P. McGibney and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Business & Economics categories.
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
Applied Regression Analysis
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Author : John O. Rawlings
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-06
Applied Regression Analysis written by John O. Rawlings and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-06 with Mathematics categories.
Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course. Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.