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(More customer reviews)There are so many great things about this book on applied regression that it is hard to know where to start. I'll mention six areas. First, the text teaches from the standpoint of someone learning rather than just presenting topics. The text goes carefully through examples that draw attention to what works and what does not work. Second, I like the chapter on extensions of regression. Third, I like the detailed steps of each hypothesis test along with the meaning of each step. Fourth, I like the thorough review of transformations of predictors and transformations of the dependent variable. Fifth, great treatment of categorical values. Sixth: good use of graphs to study whether the four assumptions of regression are met. Bottom line: if you study this book carefully and work through the examples, you will have a useful tool box to apply to a wide variety of business problems. If you are interested in this topic, I highly recommend this text. It's well worth the investment.
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An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression analysis to make informed decisions. Applied Regression Modeling: A Business Approach offers a practical, workable introduction to regression analysis for upper-level undergraduate business students, MBA students, and business managers, including auditors, financial analysts, retailers, economists, production managers, and professionals in manufacturing firms.The book's overall approach is strongly based on an abundant use of illustrations and graphics and uses major statistical software packages, including SPSS(r), Minitab(r), SAS(r), and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided, although Excel does not have a built-in capability to carry out all the techniques discussed.Applied Regression Modeling: A Business Approach offers special user features, including:* A companion Web site with all the datasets used in the book, classroom presentation slides for instructors, additional problems and ideas for organizing class time around the material in the book, and supplementary instructions for popular statistical software packages. An Instructor's Solutions Manual is also available.* A generous selection of problems-many requiring computer work-in each chapter with fullyworked-out solutions* Two real-life dataset applications used repeatedly in examples throughout the book to familiarize the reader with these applications and the techniques they illustrate* A chapter containing two extended case studies to show the direct applicability of the material* A chapter on modeling extensions illustrating more advanced regression techniques through the use of real-life examples and covering topics not normally seen in a textbook of this nature* More than 100 figures to aid understanding of the materialApplied Regression Modeling: A Business Approach fully prepares professionals and students to apply statistical methods in their decision-making, using primarily regression analysis and modeling. To help readers understand, analyze, and interpret business data and make informed decisions in uncertain settings, many of the examples and problems use real-life data with a business focus, such as production costs, sales figures, stock prices, economic indicators, and salaries. A calculus background is not required to understand and apply the methods in the book.
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