About this product

Product Identifiers

PublisherPearson Education

ISBN-100789756552

ISBN-139780789756558

eBay Product ID (ePID)219264133

Product Key Features

Number of Pages368 Pages

LanguageEnglish

Publication NameRegression Analysis Microsoft Excel

Publication Year2016

SubjectMathematical & Statistical Software, Probability & Statistics / Regression Analysis, Desktop Applications / Spreadsheets, Statistics

TypeTextbook

AuthorConrad Carlberg

Subject AreaMathematics, Computers, Business & Economics

FormatTrade Paperback

Dimensions

Item Height0.8 in

Item Weight20.5 Oz

Item Length9 in

Item Width7.2 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN2016-930324

Dewey Edition2 3

IllustratedYes

Dewey Decimal519.5/360285554

Table Of Content1 Measuring Variation: How Values Differ 2 Correlation 3 Simple Regression 4 Using the LINEST( ) Function 5 Multiple Regression 6 Assumptions and Cautions Regarding Regression Analysis 7 Using Regression to Test Differences Between Group Means

SynopsisThis 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. 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. 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. 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! Understand what regression analysis can and can't do, and why Master regression-based functions built into all recent versions of Excel Work with correlation and simple regression Make the most of Excel's improved LINEST() function Plan and perform multiple regression Distinguish the assumptions that matter from the ones that don't Extend your analysis options by using regression instead of traditional analysis of variance Add covariates to your analysis to reduce bias and increase statistical power, The author clearly explains all the theory students will need to avoid mistakes, understand what 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., This is today's most complete guide to regression analysis with Microsoft(R) 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. 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. 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. 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 Understand what regression analysis can and can't do, and why Master regression-based functions built into all recent versions of Excel Work with correlation and simple regression Make the most of Excel's improved LINEST() function Plan and perform multiple regression Distinguish the assumptions that matter from the ones that don't Extend your analysis options by using regression instead of traditional analysis of variance Add covariates to your analysis to reduce bias and increase statistical power, This is today's most complete guide to regression analysis with Microsoft(R) 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. 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. 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. 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! Understand what regression analysis can and can't do, and why Master regression-based functions built into all recent versions of Excel Work with correlation and simple regression Make the most of Excel's improved LINEST() function Plan and perform multiple regression Distinguish the assumptions that matter from the ones that don't Extend your analysis options by using regression instead of traditional analysis of variance Add covariates to your analysis to reduce bias and increase statistical power

LC Classification NumberQA278.2