Statistics and Data Science
Statistics is the art of answering complex questions from numerical facts, called data. The mathematical foundation of statistics lies in the theory of probability, which is applied to make inferences and decisions under uncertainty. Practical statistical analysis also uses a variety of computational techniques, methods of visualizing and exploring data, methods of seeking and establishing structure and trends in data, and a mode of questioning and reasoning that quantifies uncertainty. Knowledge of statistics is necessary for conducting research in the sciences, medicine, industry, business, and government.
S&DS 100, and the 101–106 group provide an introduction to statistics and data science with no mathematics prerequisite. These courses are alternatives; they do not form a sequence. Each course in the S&DS 101–106 group emphasizes applications to a particular field of study and is taught jointly by two instructors, one specializing in statistics and the other in the relevant area of application (life sciences, political science, social sciences, medicine, or data analysis). The half-term, half-credit course S&DS 109, offers the same introduction to statistics as the 101–106 group, but without applications to a specific field.
S&DS 230, emphasizes practical data analysis and the use of the computer and has no mathematics prerequisite.
For students with sufficient preparation in mathematics, S&DS 238, covers essential ideas of probability and statistics, together with an introduction to data analysis using modern computational tools.
The sequence S&DS 241 and S&DS 242, offers the mathematical foundation for the theory of probability and statistics, and is required for most higher-level courses. Some courses require only S&DS 241 as a prerequisite, including S&DS 251.