Regression Analysis Microsoft Excel

Regression Analysis Microsoft Excel

<p style="margin: 0px;">         </p> <p style="margin: 0px;">This is today’s most complete guide to regression analysis with Microsoft® Excel for any business analytics or research task. Drawing on 25 years of advanced statistical experience, Microsoft MVP Conrad Carlberg shows how to use Excel’s regression-related worksheet functions to perform a wide spectrum of practical analyses.</p> <p style="margin: 0px;"> <br> </p> <p style="margin: 0px;">Carlberg clearly explains all the theory you’ll need to avoid mistakes, understand what your regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples.</p> <p style="margin: 0px;"> <br> </p> <p style="margin: 0px;">He discusses the consequences of using each option and argument, points out idiosyncrasies and controversies associated with Excel’s regression functions, and shows how to use them reliably in fields ranging from medical research to financial analysis to operations.</p> <p style="margin: 0px;"> <br> </p> <p style="margin: 0px;">You don’t need expensive software or a doctorate in statistics to work with regression analyses. Microsoft Excel has all the tools you need—and this book has all the knowledge!</p> <p style="margin: 0px;"> <br> </p> <ul> <li> <div style="margin: 0px;">Understand what regression analysis can and can’t do, and <i>why</i> </div> </li> <li> <div style="margin: 0px;">Master regression-based functions built into all recent versions of Excel</div> </li> <li> <div style="margin: 0px;">Work with correlation and simple regression</div> </li> <li> <div style="margin: 0px;">Make the most of Excel’s improved LINEST() function</div> </li> <li> <div style="margin: 0px;">Plan and perform multiple regression</div> </li> <li> <div style="margin: 0px;">Distinguish the assumptions that matter from the ones that don’t</div> </li> <li> <div style="margin: 0px;">Extend your analysis options by using regression instead of traditional analysis of variance</div> </li> <li> <div style="margin: 0px;">Add covariates to your analysis to reduce bias and increase statistical power</div> </li> </ul> <p style="margin: 0px;"> </p>