Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.

Interpretations of the concept of probability. Basic probability rules; random variables and distribution functions; functions of random variables. Applications to quality control and the reliability assessment of mechanical/electrical components, as well as simple structures and redundant systems. Elements of statistics. Bayesian methods in engineering. Methods for reliability and risk assessment of complex systems, (event-tree and fault-tree analysis, common-cause failures, human reliability models). Uncertainty propagation in complex systems (Monte Carlo methods, Latin Hypercube Sampling). Introduction to Markov models. Examples and applications from nuclear and chemical-process plants, waste repositories, and mechanical systems. Open to qualified undergraduates.

Probability theory captures a number of essential characteristics of human cognition, including aspects of perception, reasoning, belief revision, and learning. Expressions of degree of belief were used in language long before people began codifying the laws of probability theory. This course explores the history and debates over codifying the laws of probability, how probability theory applies to specific cognitive processes, how it relates to the human understanding of causality, and how new computational approaches to causal modeling provide a framework for understanding human probabilistic reasoning. An introduction to the use of probability theory to capture aspects of cognitive processes. Emphasizes history of probability theory and computational approaches to probabilistic and causal inference. This class is suitable for advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields.

This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality; law of large numbers; and central limit theorem.

Quantitative analysis of uncertainty and risk for engineering applications. Fundamentals of probability, random processes, statistics, and decision analysis. Random variables and vectors, uncertainty propagation, conditional distributions, and second-moment analysis. Introduction to system reliability. Bayesian analysis and risk-based decision. Estimation of distribution parameters, hypothesis testing, and simple and multiple linear regressions. Poisson and Markov processes. Emphasis on application to engineering problems.

This course introduces dynamic processes and the engineering tasks of process operations and control. Subject covers modeling the static and dynamic behavior of processes; control strategies; design of feedback, feedforward, and other control structures; model-based control; and applications to process equipment.

Production of Educational Videos is an introduction to technical communication that is situated in the production of educational videos; the assignments are all focused on the production of videos that teach some aspect of MIT's first-year core curriculum. The objective of these assignments is improvement in both communication ability and communication habits; these improvements are effected by providing participants with instruction, practice, feedback, and the opportunity for reflection. In addition to improvements in communication skills, improvement is expected in students' attitude towards writing, oral presentations, and collaboration; as the semester progresses, students should feel confident of their ability to write, present, and collaborate.

Covers modern tools and methods for product design and development. The cornerstone is a project in which teams of management, engineering, and industrial design students conceive, design, and prototype a physical product. Class sessions employ cases and hands-on exercises to reinforce the key ideas. Topics include: product planning, identifying customer needs, concept generation, product architecture, industrial design, concept design, and design-for-manufacturing.

Subject engages a dialogue with architecture and urbanism from the perspective of the visual artist. Ideas investigated thematically from early modernist practices to the most recent examples of contemporary production. Art making as an adjunct to the design process is challenged by both synthetic and critical models of production. Visual art practice is examined as a conceptual prologue to architectural and urbanistic thinking, as an integrated part of the design process, and as a critical epilogue. Lectures and discussions lead to the development of realized projects to be coordinated with architectural studio. This seminar engages in the notion of space from various points of departure. The goal is first of all to engage in the term and secondly to examine possibilities of art, architecture within urban settings in order to produce what is your interpretation of space.

Sustainability challenges organizations to address the implications--and responses--in their own operations and supply chain, products/services/markets, and community responsibilities. This course exposes students to professionals and organizations who are actively working toward making their organizations and industries sustainable.

Principles of functional, imperative, and logic programming languages. Meta-circular interpreters, semantics (operational and denotational), type systems (polymorphism, inference, and abstract types), object oriented programming, modules, and multiprocessing. Case studies of contemporary programming languages. Programming experience and background in language implementation required. From the course home page: The course involves substantial programming assignments and problem sets as well as a significant amount of reading. The course uses the SCHEME+ programming language for all of its assignments.

This class builds a bridge between the recreational world of algorithmic puzzles (puzzles that can be solved by algorithms) and the pragmatic world of computer programming, teaching students to program while solving puzzles. Python syntax and semantics required to understand the code are explained as needed for each puzzle.

Explore where the prohibitions and permissions that occur in every day life come from, why they exist, and what gives them force. For example: food- you are only willing and able to eat a subset of the world's edible substances. Marriage- some marriages are prohibited by law or by custom. Addresses questions of prohibition and permission using psychological sources and literary works from ancient to modern. Includes texts by Shakespeare, Melville, Mary Rowlandson, and Anita Desai. Students give group and individual oral presentations.

Examines techniques and procedures relevant for project planning and implementation in developing countries, including project identification, feasibility analysis, design and implementation monitoring. Considers how to evaluate economic and distributive effects of completed or ongoing development projects. Specific attention given to how institutional setting and other practical influences affect the use of conventional analytical tools.

Project Evaluation covers methodologies for evaluating civil engineering projects, which typically are large-scale and long-lived and involve many economic, financial, social and environmental factors. The course places an emphasis on dealing with uncertainty. Students learn basic techniques of engineering economics, including net present value analysis, life-cycle costing, benefit-cost analysis, and other approaches to project evaluation. Examples are drawn from both contemporary and historical projects in various fields, including transportation systems, urban development, energy and environmental projects, water resource management, telecommunications systems, and other elements of the public and private projects and programs.

This is an engineering laboratory subject for mechanical engineering juniors and seniors. Major emphasis is on interplay between analytical and experimental methods in solution of research and development problems. Communication (written and oral) of results is also a strong component of the course. Groups of two or three students work together on three projects during the term.

What's it like to do mathematical research? The "Project Laboratory in Mathematics" course from MIT's OpenCourseWare provides some fine insights into this endeavor. The course was originally developed by Professor Haynes Miller and features information about how to help students "explore puzzling and complex mathematical situations." The site includes selected video lectures from the course, instructor insights, and a selection of projects and examples, such as "The Dynamics of Successive Differences Over Z and R." Also, the site includes information on how to customize this course for a variety of settings, along with examples of classroom activities and helpful resources.

1.040 Project Management focuses on the management and implementation of construction projects, primarily infrastructure projects. A project refers to a temporary piece of work undertaken to create a unique product or service. Whereas operations are continuous and repeating, projects are finite and have an end date. Projects bring form or function to ideas or need. Some notable projects include the Manhattan Project (developing the first nuclear weapon); the Human Genome Project (mapping the human genome); and the Central Artery Project (Boston's Big Dig"). The field of project management deals with the planning, execution, and controlling of projects. The course is divided into three parts: Part 1: project finance Part 2: project evaluation Part 3: project organization This course will cover the basic tools, skills, and knowledge necessary to successfully manage a project through its inception, design, planning, construction, and transition phases. There will be several guest lectures discussing current projects, and a construction site visit to MIT's Media Lab extension."

Examines alternative economic, political, and social perspectives of property rights and their policy and planning implications. Focuses on institutional and governance structures, power and control mechanisms, distributional consequences of different property rights arrangements, and problems of incomplete contracts as presented in theory and practice. Deals with property-rights issues related to two or more of the following: land, natural resources, infrastructure, or industrial organization.

Seminar covering topics of current interest in biology. Includes reading and analysis of research papers and student presentations. Contact Biology Education Office for topics. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a highly interactive setting. The instructor for this course, Dr. Kosinski-Collins, is a member of the HHMI Education Group. Maintenance of the complex three-dimensional structure adopted by a protein in the cell is vital for function. Oftentimes, as a consequence of environmental stress, genetic mutation, and/or infection, the folded structure of a protein gets altered and multiple proteins stick and fall out of solution in a process known as aggregation. In many protein aggregation diseases, incorrectly folded proteins self-associate, forming fiber-like aggregates that cause brain cell death and dementia. In this course, the molecular and biochemical basis of the prion diseases, which include bovine spongiform encephalopathy (mad cow disease), Creutzfedt-Jakob disease and kuru will be examined. Also discussed are other classes of misfolding diseases such as Alzheimer's disease and Huntington's disease. The proteins involved in all of these disorders and how the proteins' three dimensional structures change during the course of these afflictions is covered as well as why prions from certain species cannot infect animals from other species based on protein sequence and structure. The course will then address possible detection methods and therapies that are under development to treat some of the protein aggregation diseases.