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Your search for courses · during 24FA, 25WI, 25SP · tagged with SDSC Math Stats Elective · returned 6 results

MATH 240 Probability 6 credits
Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions.
 Fall 2024, Winter 2025
 FSR, Formal or Statistical Reasoning

Student has completed any of the following course(s): MATH 120 – Calculus 2 or MATH 211 – Introduction to Multivariable Calculus or greater with a grade of C or better or received a score of 4 or better on the Calculus BC AP exam or equivalent.

MATH 271 Optimization 6 credits
Optimization is all about selecting the "best" thing. Finding the most likely strategy to win a game, the route that gets you there the fastest, or the curve that most closely fits given data are all examples of optimization problems. In this course we study linear optimization (also known as linear programming), the simplex method, and duality from both a theoretical and a computational perspective. Applications will be selected from statistics, economics, computer science, and more. Additional topics in nonlinear and convex optimization will be covered as time permits.
 Spring 2025
 FSR, Formal or Statistical Reasoning

Student must have completed any of the following course(s): MATH 134 – Linear Algebra with Applications or MATH 232 – Linear Algebra AND MATH 120 – Calculus 2 or MATH 211 – Multivariable Calculus with a grade of C or better or equivalents.

STAT 250 Introduction to Statistical Inference 6 credits
Introduction to modern mathematical statistics. The mathematics underlying fundamental statistical concepts will be covered as well as applications of these ideas to reallife data. Topics include: resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodnessoffit tests, regression, and Bayesian methods. The statistical package R will be used to analyze data sets.
 Winter 2025, Spring 2025
 FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning

Student has completed any of the following course(s): MATH 240 – Probability with a grade of C or better.

STAT 270 Statistical Learning 6 credits
Statistical learning (sometimes called statistical machine learning) centers on the discovery of structural patterns and making predictions using complex data sets. This course explores supervised and unsupervised statistical learning methods, and the ethical considerations of their use. Topics may include nonparametric regression, classification, cross validation, linear model selection techniques and regularization, and clustering. Students will implement these concepts using opensource computational tools, such as the R language.
Not open to students who have received credit for CS 320
 Fall 2024
 FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning

Student has completed any of the following course(s): STAT 230 Applied Regression Analysis with a grade of C or better and has NOT taken CS 320 – Machine Learning

STAT 320 Time Series Analysis 6 credits
Models and methods for characterizing dependence in data that are ordered in time. Emphasis on univariate, quantitative data observed over evenly spaced intervals. Topics include perspectives from both the time domain (e.g., autoregressive and moving average models, and their extensions) and the frequency domain (e.g., periodogram smoothing and parametric models for the spectral density). Exposure to matrix algebra may be helpful but is not required.
 Spring 2025
 FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning

Student has completed any of the following course(s): STAT 230 – Applied Regression Analysis and STAT 250 – Introduction to Statistical Inference with a grade of C or better.

STAT 330 Advanced Statistical Modeling 6 credits
Topics include linear mixed effects models for repeated measures, longitudinal or hierarchical data and generalized linear models (of which logistic and Poisson regression are special cases) including zeroinflated Poisson models. Depending on time, additional topics could include survival analysis or generalized additive models.
 Winter 2025
 FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning

Student has completed any of the following course(s): STAT 230 – Applied Regression Analysis and STAT 250 – Introduction to Statistical Inference with a grade of C or better and has completed or is in the process of completing MATH 134 – Linear Algebra with Practical Applications or MATH 232 – Linear Algebra with a grade of C or better or equivalents.