ISTA370

035677

For some reason, the methods and tools used by the natural sciences are not taught in the information sciences. Consequently, information scientists are rarely good at designing experiments, making data give up its secrets, or quantifying their confidence in results. This course is about how to think and work like a scientist. It covers exploratory data analysis and visualization, experimental design, statistical hypothesis testing and effect size, computer intensive methods such as the bootstrap and Monte Carlo sampling, performance assessment and other performance measures, modeling complex systems, and other empirical methods for students in the information disciplines.

GRD - Regular Grades A, B, C, D, E

Undergraduate

College Algebra (MATH 109C or MATH 112) and ISTA 116.