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This undergraduate class serves as an introduction to probability and statistics, with emphasis on engineering applications. The first segment discusses events and their probability, Bayes' Theorem, discrete and continuous random variables and vectors, univariate and multivariate distributions, Bernoulli trials and Poisson point processes, and full-distribution uncertainty propagation and conditional analysis. The second segment deals with second-moment representation of uncertainty and second-moment uncertainty propagation and conditional analysis.
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Coding for the AWGN channel; block and convolutional codes; lattice and trellis codes; capacity-approaching codes; equalization of linear Gaussian channels; linear, decision-feedback, and MLSD equalization; precoding; multicarrier modulation; and topics in wireless communication. Description from the course home page: This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles.
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Fundamentals of characterizing and recognizing patterns and features of interest in numerical data. Basic tools and theory for signal understanding problems with applications to user modeling, affect recognition, speech recognition and understanding, computer vision, physiological analysis, and more. Decision theory, statistical classification, maximum likelihood and Bayesian estimation, non-parametric methods, unsupervised learning and clustering. Additional topics on machine and human learning from active research.
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Introduces students to the basic tools in using data to make informed management decisions. Covers introductory probability, decision analysis, basic statistics, regression, simulation, linear and nonlinear optimization, and discrete optimization. Computer spreadsheet exercises, cases, and examples drawn from marketing, finance, operations management, and other management functions. Restricted to first-year Sloan master's students.
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A computational and application-oriented introduction to the modeling of large-scale systems in a wide variety of decision-making domains and the optimization of such systems using state-of-the-art optimization software. Application domains include transportation and logistics, pattern classification, structural design, financial engineering, and telecommunications system planning.
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Analysis of strategic behavior in multi-person economic settings. Introduction to Nash equilibrium and its refinements: subgame-perfect equilibrium and sequential equilibrium. Applications drawn from labor economics, the economics of organization, industrial organization, international trade, and macroeconomics.
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This course addresses the challenges of defining a relationship between exposure to environmental chemicals and human disease. Course topics include epidemiological approaches to understanding disease causation; biostatistical methods; evaluation of human exposure to chemicals, and their internal distribution, metabolism, reactions with cellular components, and biological effects; and qualitative and quantitative health risk assessment methods used in the U.S. as bases for regulatory decision-making. Throughout the term, students consider case studies of local and national interest.
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The planning of sites and the infrastructure systems which serve them. Site analysis, spatial organization of uses on sites, design of roadways and subdivision patterns, grading plans, utility systems, analysis of runoff, parking requirements, traffic and off-site impacts, landscaping. Lectures on analytical techniques and examples of good site-planning practice. Assignments on each aspect of subject.
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The evolving organization and operation of real estate capital markets. Sources of real estate capital. Primary and secondary mortgage markets. The investment behavior of real estate assets. The development of REITs and securitized debt markets. Advanced pricing techniques for complex real estate securities. From the course home page: Course Description This course presents some of the major concepts, principles, analytical methods and tools useful for making investment and finance decisions regarding commercial real estate assets.
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Introduces basic economic analysis for planning students including the functioning of markets, the allocation of scarce resources among competing uses, profit maximizing behavior under different market structure, and intertemporal investment decisions.
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