This is the first semester of a two-semester sequence on Differential Analysis. Topics include fundamental solutions for elliptic; hyperbolic and parabolic differential operators; method of characteristics; review of Lebesgue integration; distributions; fourier transform; homogeneous distributions; asymptotic methods.
In this class, students use data and systems knowledge to build models of complex socio-technical systems for improved system design and decision-making. Students will enhance their model-building skills, through review and extension of functions of random variables, Poisson processes, and Markov processes; move from applied probability to statistics via Chi-squared t and f tests, derived as functions of random variables; and review classical statistics, hypothesis tests, regression, correlation and causation, simple data mining techniques, and Bayesian vs. classical statistics. A class project is required.
Subject:
Mathematics and Statistics, Science and Technology
6.780 covers statistical modeling and the control of semiconductor fabrication processes and plants. Topics include design of experiments, response surface modeling, and process optimization; defect and parametric yield modeling; process/device/circuit yield optimization; monitoring, diagnosis, and feedback control of equipment and processes; analysis and scheduling of semiconductor manufacturing operations.
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