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 readers 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.
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Table of Contents:
- 1 Making the Transition
- 2 Descriptive Statistics
- 3 Regression Analysis in Excel and R
- 4 Analysis of Variance and Covariance in Excel and R
- 5 Logistic Regression in Excel and R
- 6 Principal Components Analysis
About the Author :
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 which 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.
