Conrad Carlberg's Statistical Analysis with R and Microsoft?Excel is the first complete guide to performing modern statistical analyses with Excel, R, or both. Drawing on his immense experience helping organizations gain value from statistical methods, Carlberg shows when and how to use Excel, when and how to use R instead, and how to use them together to get the best from both. ?/P> Writing in clear, understandable English, Carlberg combines an exploration of statistical theory with a hands-on description of how to perform many common statistical analyses with both Excel and R. Through examples, you'll gain practical insights into each tool's strengths and weaknesses in a wide variety of common analytic scenarios. Coverage includes: Preparing data for analysis Performing simple descriptive analyses Using Excel and R to perform regressions Analyzing variance and covariance Running logistic regressions Analyzing time series and principal components Moving comfortably between R and Excel Statistical Analysis with R and Microsoft?Excel will be especially valuable for Excel users who: Have complex analytical problems that can't easily be solved with Excel's built-in tools Don't want to write custom Visual Basic or C code to perform advanced Excel analyses Want to combine R's power with Excel's simplicity and intuitive visual reports Want to access all the power of a professional-quality statistical package without the expense