商品簡介
Conrad Carlberg's Regression Analysis Microsoft® Excel is today's most complete guide to regression analysis with Microsoft Excel for any business analytics or research task. Drawing on his immense experience helping organizations gain value from statistical methods, Carlberg shows how to use Excel functions to reliably perform a wide spectrum of regression analysis tasks from simple correlations and t-tests through multiple analysis of covariance.
Writing in clear, understandable English, Carlberg explains all the statistical theory you'll need to avoid mistakes, understand what your regressions are really doing, and evaluate regression-based analyses performed by others. You'll learn what regression analysis can and can't do, and understand the important limits theory places on inferences that may be drawn from it.
Carlberg links theoretical understanding to hands-on, step-by-step walkthroughs of performing regressions using Microsoft Excel. He illuminates the consequences of using each option and argument associated with Excel's regression-related worksheet functions, points out idiosyncrasies and controversies associated with them, and shows how to use them reliably.
作者簡介
Conrad Carlberg (www.conradcarlberg.com) is a nationally recognized expert on Quantitative analysis and on data analysis and management applications such as Microsoft Excel, SAS, and Oracle. He holds a Ph.D. in statistics from the University of Colorado and is a many-time recipient of Microsoft’s Excel MVP designation.
Carlberg is a Southern California native. After college he moved to Colorado, where he worked for a succession of startups and attended graduate school. He spent two years in the Middle East, teaching computer science and dodging surly camels. After finishing graduate school, Carlberg worked at US West (a Baby Bell) in product management and at Motorola.
In 1995 he started a small consulting business that provides design and analysis services to companies that want to guide their business decisions by means of quantitative analysis—approaches that today we group under the term “analytics.” He enjoys writing about those techniques and, in particular, how to carry them out using the world’s most popular numeric analysis application, Microsoft Excel.
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