(Formerly MTH/PSY 201). An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

Same as CSC 109. The world is growing increasingly reliant on collecting and analyzing information to help people make decisions. Because of this, the ability to communicate effectively about data is an important component of future job prospects across nearly all disciplines. In this course, students learn the foundations of information visualization and sharpen their skills in communicating using data. Throughout the semester, we explore concepts in decision-making, human perception, color theory and storytelling as they apply to data-driven communication.

Same as SDS 109. The world is growing increasingly reliant on collecting and analyzing information to help people make decisions. Because of this, the ability to communicate effectively about data is an important component of future job prospects across nearly all disciplines. In this course, students learn the foundations of information visualization and sharpen their skills in communicating using data.