Mathematics & Statistics

• CAS MA 585: Time Series and Forecasting
  Undergraduate Prerequisites: CASMA 581 or ENGEK 381 or ENGEK 500 or consent of instructor. - Autocorrelation and partial autocorrelation functions; stationary and nonstationary processes; ARIMA and Seasonal ARIMA model identification, estimation, diagnostics, and forecasting. Modeling financial data via ARCH and GARCH models. Volatility estimation; additional topics, including long-range dependence and state-space models.
• CAS MA 586: Stochastic Methods for Algorithms
  Undergraduate Prerequisites: First-Year Writing Seminar (e.g., WR 120); and (CASCS 111 or CDSDS 110, or ENGEK 125) and (CASMA 225 or CASCS 235 or CDSDS 122) and (CASMA 242 or CASMA 442 or CASCS 132 or CDSDS 121 or ENGEK 103) and (CASMA 581 or CASCS 237 or ENGEK 381 or ENGEK 500) or consent of instructor. - Application of stochastic process theory to design and analyze algorithms used in statistics and machine learning, especially Markov chain Monte Carlo and stochastic optimization methods. Emphasizes connecting theoretical results to practice through combination of proofs, numerical experiments, and expository writing. Effective Fall 2023, this course fulfills a single unit in each of the following BU Hub areas: Writing-Intensive Course, Creativity/Innovation.
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  • Creativity/Innovation
  • Writing-Intensive Course
• CAS MA 588: Nonparametric Statistics
  Undergraduate Prerequisites: CASMA 582 or consent of instructor. - The theory and logic in the development of nonparametric techniques including order statistics, tests based on runs, goodness of fit, rank-order (for location and scale), measures of association, analysis of variance, asymptotic relative efficiency.
• CAS MA 589: Computational Statistics
  Undergraduate Prerequisites: CASMA 575 or consent of instructor. - Topics from computational statistics that are relevant to modern statistical applications: random number generation, sampling, Monte Carlo methods, computational inference, MCMC methods, graphical models, data partitioning, and bootstrapping. Emphasis on developing solid conceptual understanding of the methods through applications.
• CAS MA 592: Introduction to Causal Inference
  Undergraduate Prerequisites: CASMA 575 or consent of instructor. - Concepts and methods for causal inference. You may have heard "association does not imply causation." But, what implies causation? In this course, we study how to estimate causal effects from data. We cover both experimental and non-experimental settings..