Introduction to Statistical Data Science.

Catalog description

Semester course; 3 lecture hours. 3 credits. Prerequisites: STAT 305 or STAT 314 ; and STAT 321 . Familiarity with a computer programming language is strongly recommended. Introduces students to statistical concepts and tools of data science for processing, presenting and analyzing data. Topics include data visualization, data wrangling, simulation studies, statistical inference techniques and implementations, and other content that reflects the current needs of data scientists. The course takes an applied approach to provide a broad treatment of these topics from a statistical perspective. Students will be engaged in real data analysis using R and Python, progressing through data processing, exploratory techniques, statistical modeling, and interpreting and communicating analysis results.