2017 ~ Present

Statistics Online Computational Resource


The Statistics Online Computational Resource (SOCR) is an online collection of educational materials and tools for the use of advanced methods in probability and statistics. This team will develop an enhanced analysis and visualization toolbox for the SOCR with an emphasis on “Big Data”: very large datasets that are difficult to analyze and interpret in meaningful ways with basic probability/statistical methods. The toolbox will be designed to run in a web browser and provide enhanced visual means to present, and interpret, Big Data. The creation of the toolbox to enhance the SOCR will allow many more researchers (and students) to learn about, appreciate, and apply complex analyses to their work, making Big Data much easier to turn into “Big Results”.

Issues Involved or Addressed

Methods and Technologies

Academic Majors of Interest

  • Statistics
  • Data Science
  • Computer Science
  • Mathematics

Preferred Interests and Preparation

UI/UX design, HTML5, Javascript, Adobe Illustrator, Canvas, UI/UX design, Javascript, HTML5, WebGL, back-end server experience, Javascript, HTML5, R, statistical modeling, algorithm construction, interest in project material, willingness to develop skills.

Team Advisors

Prof. Ivo Dinov