FREE SHIPPING

on all orders of $79 or more

$3 OFF your purchase of $60 or more!
Use coupon code SATURDAY in checkout.

R for Microsoft® Excel Users Making the Transition for Statistical Analysis

, by
R for Microsoft® Excel Users Making the Transition for Statistical Analysis by Carlberg, Conrad, 9780789757852
Note: Supplemental materials are not guaranteed with Rental or Used book purchases.
  • ISBN: 9780789757852 | 0789757850
  • Cover: Paperback
  • Copyright: 11/18/2016
  • Rent Book

    (Recommended)

    $30.89
     
    Term
    Due
    Price
  • Buy New Book

    Currently Available, Usually Ships in 24-48 Hours

    $33.31
  • eBook

    Available Instantly

    Online: 365 Days

    Downloadable: Lifetime Access

    $38.39

 Microsoft Excel can perform many statistical analyses, but thousands of business users and analysts are now reaching its limits. R, in contrast, can perform virtually any imaginable analysis—if you can get over its learning curve. In R for Microsoft® Excel Users, Conrad Carlberg shows exactly how to get the most from both programs.

 

Drawing on his immense experience helping organizations apply statistical methods, Carlberg reviews how to perform key tasks in Excel, and then guides you through reaching the same outcome in R—including which packages to install and how to access them. Carlberg offers expert advice on when and how to use Excel, when and how to use R instead, and the strengths and weaknesses of each tool.

 

Writing in clear, understandable English, Carlberg combines essential statistical theory with hands-on examples reflecting real-world challenges. By the time you’ve finished, you’ll be comfortable using R to solve a wide spectrum of problems—including many you just couldn’t handle with Excel.

 

• Smoothly transition to R and its radically different user interface

• Leverage the R community’s immense library of packages

• Efficiently move data between Excel and R

• Use R’s DescTools for descriptive statistics, including bivariate analyses

• Perform regression analysis and statistical inference in R and Excel

• Analyze variance and covariance, including single-factor and factorial ANOVA

• Use R’s mlogit package and glm function for Solver-style logistic regression

• Analyze time series and principal components with R and Excel


You might also enjoy...



Please wait while the item is added to your bag...