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ST 120 Fundamentals of Statistical Inference
This non-calculus course will provide an introduction to elementary probability and an introductory survey of the standard toolkit of statistical methods. Probability topics will include: basic rules of probability; random variables; expected values; sampling distributions; central limit theorem. Statistical methods covered will include: confidence intervals and hypothesis tests for means and proportions in both the one- and two-sample settings; introduction to simple linear and multiple regression and correlation, including inference procedures for key parameters; one-way and two-way ANOVA; analysis of two-way tables for count data. Point-and-click statistical software will be used for implementation.
Typically offered in Fall and Spring
Statistics (BS)
/undergraduate/sciences/statistics/statistics-bs/
The Bachelor of Science in Statistics curriculum provides foundational training for careers in statistics and data science, and also prepares students for graduate study in statistics or related fields such as analytics. Our program's emphasis on statistical computing is unique, and prepares our graduates for careers in the rapidly evolving Data Science sector. While our curriculum is centered on statistics, mathematics, and computer programming, it is also designed to have a flexible interdisciplinary flavor. Each statistics major works with their advisor to formulate an individualized plan for 12 credits of "Advised Electives鈥�, and this plan typically leads to a minor or second major in fields including business and finance, agriculture and life sciences, computer science, industrial engineering, or the social sciences.
Statistics (BS): Data Science Concentration
/undergraduate/sciences/statistics/statistics-bs-data-science-concentration/
...or better are required for ST 115, ST 120, ST 121, MA 141, MA 241...