This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. It is especially useful for those engaged in working with numbers--preparing forecasts, budgeting, estimating the effects of business decisions, and any of the forms of analytics that have recently become so useful. This book is a nontheoretical treatment that is accessible to readers with even a limited statistical background. This book specifically does not cover the theory of regression; it is designed to teach the correct use of regression, while advising the reader of its limitations and teaching about common pitfalls. It is useful for business professionals, MBA students, and others with a desire to understand regression analysis without having to work through tedious mathematical/statistical theory. This book describes exactly how regression models are developed and evaluated. Real data are used, instead of contrived textbook-like problems. The data used in the book are the kind of data managers are faced with in the real world. Included are instructions for using Microsoft Excel to build business/economic models using regression analysis with an appendix using screen shots and step-by-step instructions. Completing this book will allow you to understand and build basic business/economic models using regression analysis. You will be able to interpret the output of those models and you will be able to evaluate the models for accuracy and shortcomings. Even if you never build a model yourself, at some point in your career it is likely that you will find it necessary to interpret one; this book will make that possible.
His profit , if he wins , equals v - s . Hence his expected profit is simply 2s ( v – s ) . This function takes its maximum at the point s = v / 2 , as is easily checked by difBox 2.2 ( continued ) 1 ( c ) ( b Some Models That Work 53.
本书围绕20世纪80年代以来的时间序列分析方法的研究成果,着重讨论适用于经济时间序列分析的各种非线性时间序列模型及其应用实践。本书在说明时间序列分析的基本概念与非线性 ...
Following Leontief , Rosenberg ( 1992 , p . 65 ) allows that agricultural economics has exhibited substantial predictive improvement . But Rosenberg discounts this on the ground that the confirmed predictions in agricultural economics ...
The purpose of this booklet is to introduce readers to the appropriate econometric techniques for use with different forms of survey data - known collectively as microeconometrics.
Statistics and Econometric Models: Testing, confidence regions, model selection, and asymptotic theory ; Christian Gourieroux, Alain Monfort ; translated by...
[ 83 ] J. Durbin , Maximum Likelihood Estimation of the Parameters of a System of Simultaneous Regression Equations ... [ 97 ] R.C. Fair , Specification , Estimation , and Analysis of Macroeconometric Models , Harvard University Press ...
Cette 7e édition, mise à jour et enrichie d'un nouveau chapitre, présente de façon extrêmement pédagogique les concepts de l'économétrie moderne et plus particulièrement : les domaines classiques de l'économétrie (modèle ...
For advanced undergraduate/graduate- level courses in Econometrics. This text surveys the theories, techniques (model-building and data collection), and applications of econometrics.
An attempt has been made in this work to provide a selective set of contributions on economic thinking in their applied aspects. Prof.
After a single semester spent mastering the material presented in this book, students will be prepared to take any of the many elective courses that use econometric techniques. * Requires no background in probability and statistics * ...