Prereq: MA 109 or equiv. for graduate students; undergraduates must have consent of instructor. Credit from this course applies to the following programs: Undergraduate, Graduate, Graduate Professional.
Use of statistical programming languages R and SAS to gain insight into statistical theory, to better understand fundamental statistical concepts, and to visualize data appropriately. Sampling distributions, confidence intervals and p-values, the central limit theorem, expectation, and maximum likelihood estimation. Simulation studies, data management, editing data, running basic statistical procedures, and producing reports.
Use of statistical programming languages R and SAS to gain insight into statistical theory, to better understand fundamental statistical concepts, and to visualize data appropriately. Sampling distributions, confidence intervals and p-values, the central limit theorem, expectation, and maximum likelihood estimation. Simulation studies, data management, editing data, running basic statistical procedures, and producing reports.