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STAT 220.00 Introduction to Data Science 6 credits

Open: Size: 30, Registered: 25, Waitlist: 0

CMC 102

Synonym: 61447

Adam Loy

(Formerly Mathematics 285) This course will cover the computational side of data analysis, including data acquisition, management, and visualization tools. Topics may include: data scraping, data wrangling, data visualization using packages such as ggplots, interactive graphics using tools such as Shiny, supervised and unsupervised classification methods, and understanding and visualizing spatial data. We will use the statistics software R in this course.

Prerequisite: Statistics 120 (formerly Mathematics 215), Statistics 230 (formerly Mathematics 245) or Statistics 250 (formerly Mathematics 275)

Formerly Mathematics 285

STAT 340.00 Bayesian Statistics 6 credits

Closed: Size: 20, Registered: 25, Waitlist: 0

CMC 206

Synonym: 61454

Adam Loy

Formerly MATH 315) An introduction to statistical inference and modeling in the Bayesian paradigm. Topics include Bayes’ Theorem, common prior and posterior distributions, hierarchical models, Markov chain Monte Carlo methods (e.g., the Metropolis-Hastings algorithm and Gibbs sampler) and model adequacy and posterior predictive checks. The course uses R extensively for simulations.

Prerequisite: Statistics 250 (formerly Mathematics 275)

Fomerly Mathematics 315

STAT 400.02 Integrative Exercise 3 credits, S/CR/NC only

Closed: Size: 4, Registered: 4, Waitlist: 0

CMC 209

Synonym: 61457

Adam Loy

Either a supervised small-group research project or an individual, independent reading. Required of all senior majors.

Prerequisite: Senior Statistics major. Students are strongly encouraged to complete Statistics 230 (formerly Mathematics 245) and Statistics 250 (formerly Mathematics 275) before starting this course

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You must take 6 credits of each of these.
You must take 6 credits of each of these,
except Quantitative Reasoning, which requires 3 courses.
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