My favorite tool for data analysis is the R programming language because it has a great community, it is free, and it works on Windows, Mac, and Linux. I also highly recommend RStudio if you're not into using ESS with Emacs. RStudio is great for academics because it also serves as a LaTeX editor so you can use one tool for your entire research project soup to nuts. Microsoft offers a paid support option for commercial use but there is a free and open source version.

I learned R on my own but I could not have done it without the help of sites like Stack Overflow and the outstanding R community. Before posting any questions on the web, please attempt to work the problem yourself so that people don't waste their time answering questions that have already been explained. More succinct: RTFM

Students: Download Introduction to Finance Analytics in my library and follow the directions to install R and RStudio

Installation and Introduction

  • Command Line - some problems are best solved with command line tools rather than a programming language
  • Emacs and ESS on Mac
  • Pandas - financial data analysis in Python

Econometrics

  • Regression in Excel - an absurdly short introduction to linear regression in Excel
  • Refer to the single page explanation at the end of Introduction to Finance Analytics
  • Regression in R - short command for ordinary least squares regression
  • Robust Regression in R
  • Quantile Regression in R
  • Time-Series Bootstrap

Data Manipulation and Presentation

More Advanced Stuff