Fundamentals of Statistical Data Science Introduction to computing for data analysis and visualization, and simulation, using a high-level language (e.g., R). Computational reasoning, computationally intensive statistical methods, reading tabular and non-standard data
Goals: Students become proficient in data manipulation and exploratory data analysis, and finding and conveying features of interest. They learn to map mathematical descriptions of statistical procedures to code, decompose a problem into sub-tasks, and to create reusable functions. They develop ability to transform complex data as text into data structures amenable to analysis. They learn how and why to simulate random processes, and are introduced to statistical methods they do not see in other courses.