Crop research generally involves the use of statistical techniques to generate efficient designs for data collection and to draw valid conclusions from appropriate data analysis. Much commercial and free software for statistical analysis are available. However, most commercial software are developed for general statistical analysis and are costly or difficult to use, whereas the freeware only has very limited functions. R is a language and an environment for statistical computing and graphics that has become increasingly popular. Many classical and modern statistical methods have been well implemented in R, mainly through hundreds of add-on packages contributed by leading statisticians. New add-on packages can be rapidly developed by exploring the functions of existing packages. However, some users find R’s command line interface challenging. Software with a graphical user interface (GUI) involving menus, dialog boxes, and spreadsheets is generally more preferred. STAR is developed using Eclipse Rich Client Platform (RCP) and R language for crop scientists and has a user-friendly graphical user interface (GUI). Its current version provides modules for generating randomization and layout of experimental designs commonly used in crop research, data management, and basic statistical analysis, including descriptive statistics, hypothesis testing, and ANOVA of designed experiments. In the future, modules for mixed models, combined analysis, general linear models and multivariate analysis will also be included.