The amount of data in the world is vast and is increasing exponentially. It is easy to become overwhelmed and lose sight of the goal of data: to answer questions we have about the world in a specific, concise manner. The goal of this course is to help craft answerable questions—and then answer them. In order to do this, we will be using a programming language (“R”) to help us organize data, make clean, clear graphs, and help with appropriate analysis of the data.
This course will serve two main goals. The first is an introductory statistics course: gain knowledge of the basic statistical tests, how to interpret their results in a reasonable manner, and understand what those tests are doing at a conceptual level. The second is to learn the computational language of R: how to sort, shape, and handle data, create simulations and interpret the results, and build clean, clear graphical representations of the data presented.
This course is taught at the introductory level and has no prerequisites, but does require a significant amount of time and energy outside of the classroom as we are working towards the two aforementioned goals at once. This course is appropriate for students who plan to seriously create and analyze their own statistics for their work. It may be taken alone, or as a sequel to MAT 2246 Presentation of Statistics (or to MAT 2248 and 2249, Confidently Unsure and Graphical Persuasion). There is some overlap between the courses, but their focus and goals are different. Students who take Presentation of Statistics (or Confidently Unsure/Graphical Persuasion) first will get a broader skill set and a more gentle introduction.
Learning Outcomes:
Delivery Method: Hybrid in-person and remote, with faculty in-person
Prerequisites:None.
Course Level: 2000-level
Credits: 4
T, Th 6:30PM-8:30PM (Full-term)
Maximum Enrollment: 16
Course Frequency: Once a year
Categories: All courses , Hybrid In-Person and Remote , Mathematics
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