With the increased popularity of high-level statistical programming language and environments for data analysis like R, a way to interface this package is becoming a must have for Smalltalk, since it implements complex and unrivalled statistical techniques for data manipulation and presentation, like Analysis of Variance, Covariance, Time Series, Generalized Linear Models, Additive Models, Non-linear Regressions, Tree Models, Multivariate Statistics, etc. besides the many mathematical functions, which are used in fields from economics to medicine and engineering. It is estimated that R posseses about 2 million of users worldwide and more than 2000 add-ons and increasing everyday through repositories like CRAN and Crantastic.org
The student should know or be motivated to learn statistics with the R environment and language, and its fundamental workflow: importing and preparing the data, and finally running the analysis, and presenting the results. Dealing with R sessions and presentation of results (like vectors and plots) will be challenging too.
Benefits to the Student
The student will gain invaluable experience from two complementary environments, and his experience with the interface technology choosed will be useful for the many projects where Smalltalk needs help from external systems.
Benefits to the Community
The goal of this project is to build a wrapper to interface R, an open source statistical programming language, providing a whole range of missing functionality to Smalltalk. This binding could complement the R environment where a general programming environment is needed, attracting many statisticians, and will open Smalltalk to domain-specific areas as diverse as Clinical Trials, Finance and Machine Learning.