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14.13 Economics and Psychology (MIT) 14.13 Economics and Psychology (MIT)

Description

This course integrates psychological insights into economic models of behavior. It discusses the limitations of standard economic models and surveys the ways in which psychological experiments have been used to learn about preferences, cognition, and behavior. Topics include: trust, vengeance, fairness, impatience, impulsivity, bounded rationality, learning, reinforcement, classical conditioning, loss-aversion, over-confidence, self-serving biases, cognitive dissonance, altruism, subjective well-being, and hedonic adaptation. Economic concepts such as equilibrium, rational choice, utility maximization, Bayesian beliefs, game theory, and behavior under uncertainty are discussed in light of these phenomena. This course integrates psychological insights into economic models of behavior. It discusses the limitations of standard economic models and surveys the ways in which psychological experiments have been used to learn about preferences, cognition, and behavior. Topics include: trust, vengeance, fairness, impatience, impulsivity, bounded rationality, learning, reinforcement, classical conditioning, loss-aversion, over-confidence, self-serving biases, cognitive dissonance, altruism, subjective well-being, and hedonic adaptation. Economic concepts such as equilibrium, rational choice, utility maximization, Bayesian beliefs, game theory, and behavior under uncertainty are discussed in light of these phenomena.Subjects

behavioral economics | behavioral economics | finance | finance | psychology | psychology | prospect | prospect | prospect theory | prospect theory | bias | bias | probabilistic judgment | probabilistic judgment | self-control | self-control | mental accounting | mental accounting | fairness | fairness | altruism | altruism | public goods | public goods | market anomalies | market anomalies | market theories | market theories | economics | economics | behavior | behavior | preferences | preferences | cognition | cognition | trust | trust | vengence | vengence | impatience | impatience | impulsivity | impulsivity | bounded rationality | bounded rationality | learning | learning | reinforcement | reinforcement | classical conditioning | classical conditioning | loss-aversion | loss-aversion | over-confidence | over-confidence | self-serving biases | self-serving biases | cognitive dissonance | cognitive dissonance | subjective well-being | subjective well-being | hedonic adaptation | hedonic adaptation | equilibrium | equilibrium | rational choice | rational choice | utility maximization | utility maximization | Bayesian beliefs | Bayesian beliefs | game theory | game theory | neuroeconomics | neuroeconomicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This open educational resource was released through the Higher Education Academy Engineering Subject Centre Open Engineering Resources Pilot project. The project was funded by HEFCE and the JISC/HE Academy UKOER programme.Subjects

bipolar junction transistors | dc | bias | bipolar junction | application of semi conductor devices amplifiers | metal oxide | ukoer | engscoer | metal oxide semiconductor field effect transistor | field effect transistor | resistor | jugfet | engsc | newportunioer | semi conductor | oer | collector base bias | voltage | beng | electronics | semi conductors | transistors | circuit | electrical and electronic principals | current | four resistor bias | supply base bias | electrons | semi conductor devices | university of wales | mosfet | feedback | ac | junction field effect transistor | foundation degree | amplifiers | jfet | 2009 | bjt | capacitors | hn | bipolar | fet | acdc | engineering | electrical | newport | Engineering | H000License

Attribution 2.0 UK: England & Wales Attribution 2.0 UK: England & Wales http://creativecommons.org/licenses/by/2.0/uk/ http://creativecommons.org/licenses/by/2.0/uk/Site sourced from

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This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation. This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.Subjects

system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification | system identification | estimation | estimation | least squares estimation | least squares estimation | Kalman filter | Kalman filter | noise dynamics | noise dynamics | system representation | system representation | function approximation theory | function approximation theory | neural nets | neural nets | radial basis functions | radial basis functions | wavelets | wavelets | volterra expansions | volterra expansions | informative data sets | informative data sets | persistent excitation | persistent excitation | asymptotic variance | asymptotic variance | central limit theorem | central limit theorem | model structure selection | model structure selection | system order estimate | system order estimate | maximum likelihood | maximum likelihood | unbiased estimates | unbiased estimates | Cramer-Rao lower bound | Cramer-Rao lower bound | Kullback-Leibler information distance | Kullback-Leibler information distance | Akaike?s information criterion | Akaike?s information criterion | experiment design | experiment design | model validation | model validationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.121 Microeconomic Theory I (MIT) 14.121 Microeconomic Theory I (MIT)

Description

This half-semester course provides an introduction to microeconomic theory designed to meet the needs of students in the economics Ph.D. program. Some parts of the course are designed to teach material that all graduate students should know. Others are used to introduce methodologies. Topics include consumer and producer theory, markets and competition, general equilibrium, and tools of comparative statics and their application to price theory. Some topics of recent interest may also be covered. This half-semester course provides an introduction to microeconomic theory designed to meet the needs of students in the economics Ph.D. program. Some parts of the course are designed to teach material that all graduate students should know. Others are used to introduce methodologies. Topics include consumer and producer theory, markets and competition, general equilibrium, and tools of comparative statics and their application to price theory. Some topics of recent interest may also be covered.Subjects

microeconomic theory | microeconomic theory | demand theory | demand theory | producer theory; partial equilibrium | producer theory; partial equilibrium | competitive markets | competitive markets | general equilibrium | general equilibrium | externalities | externalities | Afriat's theorem | Afriat's theorem | pricing | pricing | robust comparative statics | robust comparative statics | utility theory | utility theory | properties of preferences | properties of preferences | choice as primitive | choice as primitive | revealed preference | revealed preference | classical demand theory | classical demand theory | Kuhn-Tucker necessary conditions | Kuhn-Tucker necessary conditions | implications of Walras?s law | implications of Walras?s law | indirect utility functions | indirect utility functions | theorem of the maximum (Berge?s theorem) | theorem of the maximum (Berge?s theorem) | expenditure minimization problem | expenditure minimization problem | Hicksian demands | Hicksian demands | compensated law of demand | compensated law of demand | Slutsky substitution | Slutsky substitution | price changes and welfare | price changes and welfare | compensating variation | compensating variation | and welfare from new goods | and welfare from new goods | price indexes | price indexes | bias in the U.S. consumer price index | bias in the U.S. consumer price index | integrability | integrability | demand aggregation | demand aggregation | aggregate demand and welfare | aggregate demand and welfare | Frisch demands | Frisch demands | and demand estimation | and demand estimation | increasing differences | increasing differences | producer theory applications | producer theory applications | the LeCh?telier principle | the LeCh?telier principle | Topkis? theorem | Topkis? theorem | Milgrom-Shannon monotonicity theorem | Milgrom-Shannon monotonicity theorem | monopoly pricing | monopoly pricing | monopoly and product quality | monopoly and product quality | nonlinear pricing | nonlinear pricing | and price discrimination | and price discrimination | simple models of externalities | simple models of externalities | government intervention | government intervention | Coase theorem | Coase theorem | Myerson-Sattherthwaite proposition | Myerson-Sattherthwaite proposition | missing markets | missing markets | price vs. quantity regulations | price vs. quantity regulations | Weitzman?s analysis | Weitzman?s analysis | uncertainty | uncertainty | common property externalities | common property externalities | optimization | optimization | equilibrium number of boats | equilibrium number of boats | welfare theorems | welfare theorems | uniqueness and determinacy | uniqueness and determinacy | price-taking assumption | price-taking assumption | Edgeworth box | Edgeworth box | welfare properties | welfare properties | Pareto efficiency | Pareto efficiency | Walrasian equilibrium with transfers | Walrasian equilibrium with transfers | Arrow-Debreu economy | Arrow-Debreu economy | separating hyperplanes | separating hyperplanes | Minkowski?s theorem | Minkowski?s theorem | Existence of Walrasian equilibrium | Existence of Walrasian equilibrium | Kakutani?s fixed point theorem | Kakutani?s fixed point theorem | Debreu-Gale-Kuhn-Nikaido lemma | Debreu-Gale-Kuhn-Nikaido lemma | additional properties of general equilibrium | additional properties of general equilibrium | Microfoundations | Microfoundations | core | core | core convergence | core convergence | general equilibrium with time and uncertainty | general equilibrium with time and uncertainty | Jensen?s inequality | Jensen?s inequality | and security market economy | and security market economy | arbitrage pricing theory | arbitrage pricing theory | and risk-neutral probabilities | and risk-neutral probabilities | Housing markets | Housing markets | competitive equilibrium | competitive equilibrium | one-sided matching house allocation problem | one-sided matching house allocation problem | serial dictatorship | serial dictatorship | two-sided matching | two-sided matching | marriage markets | marriage markets | existence of stable matchings | existence of stable matchings | incentives | incentives | housing markets core mechanism | housing markets core mechanismLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.452 Economic Growth (MIT) 14.452 Economic Growth (MIT)

Description

This half semester class presents an introduction to macroeconomic modeling, focusing on the theory of economic growth and some of its applications. It will introduce a number of models of non-stochastic and stochastic macroeconomic equilibrium. It will use these models to shed light both on the process of economic growth at the world level and on sources of income and growth differences across countries. This half semester class presents an introduction to macroeconomic modeling, focusing on the theory of economic growth and some of its applications. It will introduce a number of models of non-stochastic and stochastic macroeconomic equilibrium. It will use these models to shed light both on the process of economic growth at the world level and on sources of income and growth differences across countries.Subjects

economic growth | economic growth | development | development | modern | modern | world income distribution | world income distribution | Solow growth model | Solow growth model | income differences | income differences | neoclassical growth | neoclassical growth | optimal and competitive allocations | optimal and competitive allocations | welfare theorems | welfare theorems | overlapping generations | overlapping generations | dynamic efficiency | dynamic efficiency | growth under uncertainty | growth under uncertainty | incomplete markets | incomplete markets | neoclassical endogenous growth | neoclassical endogenous growth | capital accumulation | capital accumulation | externalities | externalities | human capital | human capital | endogenous growth | endogenous growth | expanding input varieties | expanding input varieties | directed technical change | directed technical change | endogenous skill-bias technological change | endogenous skill-bias technological change | endogenous labor-augmenting technological change | endogenous labor-augmenting technological change | interdependences | interdependences | technology diffusion | technology diffusion | open economy | open economy | trade | tradeLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.13 Economics and Psychology (MIT)

Description

This course integrates psychological insights into economic models of behavior. It discusses the limitations of standard economic models and surveys the ways in which psychological experiments have been used to learn about preferences, cognition, and behavior. Topics include: trust, vengeance, fairness, impatience, impulsivity, bounded rationality, learning, reinforcement, classical conditioning, loss-aversion, over-confidence, self-serving biases, cognitive dissonance, altruism, subjective well-being, and hedonic adaptation. Economic concepts such as equilibrium, rational choice, utility maximization, Bayesian beliefs, game theory, and behavior under uncertainty are discussed in light of these phenomena.Subjects

behavioral economics | finance | psychology | prospect | prospect theory | bias | probabilistic judgment | self-control | mental accounting | fairness | altruism | public goods | market anomalies | market theories | economics | behavior | preferences | cognition | trust | vengence | impatience | impulsivity | bounded rationality | learning | reinforcement | classical conditioning | loss-aversion | over-confidence | self-serving biases | cognitive dissonance | subjective well-being | hedonic adaptation | equilibrium | rational choice | utility maximization | Bayesian beliefs | game theory | neuroeconomicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata2.160 Identification, Estimation, and Learning (MIT)

Description

This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.Subjects

system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification | estimation | least squares estimation | Kalman filter | noise dynamics | system representation | function approximation theory | neural nets | radial basis functions | wavelets | volterra expansions | informative data sets | persistent excitation | asymptotic variance | central limit theorem | model structure selection | system order estimate | maximum likelihood | unbiased estimates | Cramer-Rao lower bound | Kullback-Leibler information distance | Akaike?s information criterion | experiment design | model validationLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.63J System Safety (MIT) 16.63J System Safety (MIT)

Description

This class introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems. This class introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems.Subjects

16.63 | 16.63 | ESD.03 | ESD.03 | hazard analysis | hazard analysis | system safety | system safety | accident analysis | accident analysis | design for safety | design for safety | accident causality mode | accident causality mode | hindsight bias | hindsight bias | accident report | accident report | occupational safety | occupational safety | CAST analysis | CAST analysis | human factors | human factors | safety control structure | safety control structure | operations | operations | safety management | safety management | critical projects | critical projects | STPA hazard analysis | STPA hazard analysis | STAMP | STAMPLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.13 Economics and Psychology (MIT)

Description

This course integrates psychological insights into economic models of behavior. It discusses the limitations of standard economic models and surveys the ways in which psychological experiments have been used to learn about preferences, cognition, and behavior. Topics include: trust, vengeance, fairness, impatience, impulsivity, bounded rationality, learning, reinforcement, classical conditioning, loss-aversion, over-confidence, self-serving biases, cognitive dissonance, altruism, subjective well-being, and hedonic adaptation. Economic concepts such as equilibrium, rational choice, utility maximization, Bayesian beliefs, game theory, and behavior under uncertainty are discussed in light of these phenomena.Subjects

behavioral economics | finance | psychology | prospect | prospect theory | bias | probabilistic judgment | self-control | mental accounting | fairness | altruism | public goods | market anomalies | market theories | economics | behavior | preferences | cognition | trust | vengence | impatience | impulsivity | bounded rationality | learning | reinforcement | classical conditioning | loss-aversion | over-confidence | self-serving biases | cognitive dissonance | subjective well-being | hedonic adaptation | equilibrium | rational choice | utility maximization | Bayesian beliefs | game theory | neuroeconomicsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadataLeverhulme Lecture 2: Moral Responsibility and Implicit Bias

Description

The second of the two 2016 Leverhulme Lectures by Professor Neil Levy on the topic of implicit bias Should people be blamed for wrongful actions caused by implicit bias? That depends on how exactly these states cause behaviour, how appropriate it is to identify the agent with these states and their opportunities for controlling their influence over their behaviour. I argue that under many circumstances, the states do not belong to the agent in kind of way that makes it appropriate to identify the agent with them and that they lack responsibility-conferring control over their influences on behaviour. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/License

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See all metadataLeverhulme Lecture 1: The Nature and the Significance of Implicit Bias

Description

The first of the two 2016 Leverhulme Lectures by Professor Neil Levy on the topic of implicit bias People who sincerely express a commitment to equality sometimes act in ways that seem to belie that commitment. There is good evidence that these actions are sometimes caused by implicit mental states, of which people may not be aware. In this lecture, I introduce these states, explore how significant a role they play in explaining behaviour, and how they can be changed. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/License

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See all metadata14.127 Behavioral Economics and Finance (MIT) 14.127 Behavioral Economics and Finance (MIT)

Description

This course surveys research which incorporates psychological evidence into economics. Topics include: prospect theory, biases in probabilistic judgment, self-control and mental accounting with implications for consumption and savings, fairness, altruism, and public goods contributions, financial market anomalies and theories, impact of markets, learning, and incentives, and memory, attention, categorization, and the thinking process. This course surveys research which incorporates psychological evidence into economics. Topics include: prospect theory, biases in probabilistic judgment, self-control and mental accounting with implications for consumption and savings, fairness, altruism, and public goods contributions, financial market anomalies and theories, impact of markets, learning, and incentives, and memory, attention, categorization, and the thinking process.Subjects

behavioral economics | behavioral economics | finance | finance | psychology | psychology | prospect theory | prospect theory | bias | bias | probabilistic judgment | probabilistic judgment | self-control | self-control | mental accounting | mental accounting | fairness | fairness | altruism | altruism | public goods | public goods | market anomalies | market anomalies | market theories | market theories | heuristics | heuristics | noise | noise | confusion | confusion | competition | competition | bounded rationality | bounded rationality | learning | learning | games | games | neuroeconomics | neuroeconomics | hyperbolic discounting | hyperbolic discounting | consumption | consumption | hyperbolics | hyperbolics | temptation | temptation | assets | assets | puzzles | puzzles | bubbles | bubbles | Gul-Pesendorfer | Gul-PesendorferLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata21L.310 Bestsellers: The Memoir (MIT) 21L.310 Bestsellers: The Memoir (MIT)

Description

What is a "life" when it's written down? How does memory inform the present? Why are memoirs so popular? This course will address these questions and others, considering the relationship between biography, autobiography, and memoir and between personal and social themes. We will closely examine some recent memoirs: Tobias Wolff's This Boy's Life, Barack Obama's Dreams From My Father, Edwidge Danticat's Brother, I'm Dying, Ayaan Hirsi Ali's Infidel, and Alison Bechdel's Fun Home. Students will write two brief papers: a critical essay and an experiment in memoir.As a "Sampling," this class offers 6 units, with a strong emphasis on close reading, group discussion, focused writing, and research and presentation skills. What is a "life" when it's written down? How does memory inform the present? Why are memoirs so popular? This course will address these questions and others, considering the relationship between biography, autobiography, and memoir and between personal and social themes. We will closely examine some recent memoirs: Tobias Wolff's This Boy's Life, Barack Obama's Dreams From My Father, Edwidge Danticat's Brother, I'm Dying, Ayaan Hirsi Ali's Infidel, and Alison Bechdel's Fun Home. Students will write two brief papers: a critical essay and an experiment in memoir.As a "Sampling," this class offers 6 units, with a strong emphasis on close reading, group discussion, focused writing, and research and presentation skills.Subjects

life | life | memory | memory | memoirs | memoirs | biography | biography | autobiography | autobiography | Tobias Wolff | Tobias Wolff | Barack Obama | Barack Obama | Edwidge Danticat | Edwidge Danticat | Brother | Brother | Ayaan Hirsi Ali | Ayaan Hirsi Ali | Alison Bechdel | Alison BechdelLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata9.71 Functional MRI of High-Level Vision (MIT) 9.71 Functional MRI of High-Level Vision (MIT)

Description

We are now at an unprecedented point in the field of neuroscience: We can watch the human brain in action as it sees, thinks, decides, reads, and remembers. Functional magnetic resonance imaging (fMRI) is the only method that enables us to monitor local neural activity in the normal human brain in a noninvasive fashion and with good spatial resolution. A large number of far-reaching and fundamental questions about the human mind and brain can now be answered using straightforward applications of this technology. This is particularly true in the area of high-level vision, the study of how we interpret and use visual information including object recognition, mental imagery, visual attention, perceptual awareness, visually guided action, and visual memory. The goals of this course are to help We are now at an unprecedented point in the field of neuroscience: We can watch the human brain in action as it sees, thinks, decides, reads, and remembers. Functional magnetic resonance imaging (fMRI) is the only method that enables us to monitor local neural activity in the normal human brain in a noninvasive fashion and with good spatial resolution. A large number of far-reaching and fundamental questions about the human mind and brain can now be answered using straightforward applications of this technology. This is particularly true in the area of high-level vision, the study of how we interpret and use visual information including object recognition, mental imagery, visual attention, perceptual awareness, visually guided action, and visual memory. The goals of this course are to helpSubjects

functional magnetic resonance imaging (fMRI) | functional magnetic resonance imaging (fMRI) | neural activity | neural activity | human | human | brain | brain | noninvasive | noninvasive | resolution | resolution | high-level vision | high-level vision | object recognition | object recognition | visual attention | visual attention | perceptual awareness | perceptual awareness | visually guided action | visually guided action | visual memory | visual memory | voxelwise analysis | voxelwise analysis | conjugate mirroring | conjugate mirroring | interleaved stimulus presentation | interleaved stimulus presentation | magnetization following excitation | magnetization following excitation | active voxels | active voxels | scanner drift | scanner drift | trial sorting | trial sorting | collinear factors | collinear factors | different model factors | different model factors | mock scanner | mock scanner | scanner session | scanner session | visual stimulation task | visual stimulation task | hemoglobin signal | hemoglobin signal | labeling plane | labeling plane | nearby voxels | nearby voxels | shimming coils | shimming coils | bias field estimation | bias field estimation | conscious encoding | conscious encoding | spiral imaging | spiral imaging | functional resolution | functional resolution | hemodynamic activity | hemodynamic activity | direct cortical stimulation | direct cortical stimulation | physiological noise | physiological noise | refractory effects | refractory effects | independent statistical tests. | independent statistical tests.License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata14.452 Economic Growth (MIT) 14.452 Economic Growth (MIT)

Description

This half semester class presents an introduction to macroeconomic modeling, focusing on the theory of economic growth and some of its applications. It will introduce a number of models of non-stochastic and stochastic macroeconomic equilibrium. It will use these models to shed light both on the process of economic growth at the world level and on sources of income and growth differences across countries. This half semester class presents an introduction to macroeconomic modeling, focusing on the theory of economic growth and some of its applications. It will introduce a number of models of non-stochastic and stochastic macroeconomic equilibrium. It will use these models to shed light both on the process of economic growth at the world level and on sources of income and growth differences across countries.Subjects

economic growth | economic growth | development | development | modern | modern | world income distribution | world income distribution | Solow growth model | Solow growth model | income differences | income differences | neoclassical growth | neoclassical growth | optimal and competitive allocations | optimal and competitive allocations | welfare theorems | welfare theorems | overlapping generations | overlapping generations | dynamic efficiency | dynamic efficiency | growth under uncertainty | growth under uncertainty | incomplete markets | incomplete markets | neoclassical endogenous growth | neoclassical endogenous growth | capital accumulation | capital accumulation | externalities | externalities | human capital | human capital | endogenous growth | endogenous growth | expanding input varieties | expanding input varieties | Schumpeterian models | Schumpeterian models | endogenous skill-bias technological change | endogenous skill-bias technological change | endogenous labor-augmenting technological change | endogenous labor-augmenting technological change | interdependences | interdependences | technology diffusion | technology diffusion | open economy | open economy | trade | tradeLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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The course will focus primarily on contemporary discourses concerning gender inequality. Most of the readings assigned will be recent articles published in U.S. and British media capturing the latest thinking and research on gender inequality in the workplace. The class will be highly interactive combining case studies, videos, debates, guest speakers, and in-class simulations. The course will focus primarily on contemporary discourses concerning gender inequality. Most of the readings assigned will be recent articles published in U.S. and British media capturing the latest thinking and research on gender inequality in the workplace. The class will be highly interactive combining case studies, videos, debates, guest speakers, and in-class simulations.Subjects

gender inequality | gender inequality | wage gap | wage gap | gender gap | gender gap | diversity | diversity | parental leave | parental leave | affirmative action | affirmative action | childcare | childcare | bias | bias | stereotypes | stereotypesLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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Humans show a bias to favour information related to themselves over information related to other people. How does this effect arise? Are self biases a stable trait of the individual? Do these biases change fundamental perceptual processes? I will review recent work from my laboratory showing that self-biases modulate basic perceptual processes; they are stable for an individual and are difficult to control; they reflect rapid tuning of brain circuits to enhance the saliency of self-related items. I discuss the implications of this work for understanding whether perceptual processes are informationally encapsulated, and whether perception changes as a function of social context. Wales; http://creativecommons.org/licenses/by-nc-sa/2.0/uk/License

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Image from ?By-Roads and Battle-Fields in Picardy; with incidents and gatherings by the way between Ambleteuse and Ham; including Agincourt and Cre?cy. With illustrations?, 002593451 page 327 by MUSGRAVE, George Musgrave.Year: 1861, Place: London Publisher:Subjects

bldigital | bl_labs | britishlibrary | 1861 | similar_to_62847886830_place_of_publishing | similar_to_62847886830_bubblyness_y | similar_to_62847886830_hbias | similar_to_62847886830_vbiasLicense

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Image from ?The Lady of the Forest. [A novel.]?, 002441156 page 139 by MEADE, afterwards SMITH, Elizabeth Thomasina.Year: 1889, Place: pp. 318. Partridge & Co.: London, [1889.] Publisher:Subjects

bldigital | bl_labs | britishlibrary | 1889 | similar_to_62837577298_published_date | similar_to_62837577298_slantyness | similar_to_62837577298_hbias | similar_to_62837577298_vbias | landscapeLicense

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Image from ?Wanderings, South and East ? With two maps and forty-seven wood engravings executed under the direction of Edward Whymper, from sketches by the author, native drawings, etc?, 000779255 page 210 by COOTE, Walter.Year: 1882, Place: London Publisher: Sampson Low, Marston, Searle & RivingtonSubjects

bldigital | bl_labs | britishlibrary | 1882 | similar_to_62827584690_published_date | similar_to_62827584690_hbias | similar_to_62827584690_vbiasLicense

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Prerequisites: 14.121, 14.122Topics include: Agricultural issues: peasant behavior, land tenancy, and interlinked markets. Credit and insurance market problems and institutions. Health, nutrition, and productivity. Gender bias. Education. Technological change. Government failures. Prerequisites: 14.121, 14.122Topics include: Agricultural issues: peasant behavior, land tenancy, and interlinked markets. Credit and insurance market problems and institutions. Health, nutrition, and productivity. Gender bias. Education. Technological change. Government failures.Subjects

Agricultural issues | Agricultural issues | peasant behavior | peasant behavior | land tenancy | land tenancy | interlinked markets | interlinked markets | Credit market | Credit market | insurance market | insurance market | Health | Health | nutrition | nutrition | productivity | productivity | Gender bias | Gender bias | Education | Education | Technological change | Technological change | Government failures | Government failuresLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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This course examines the fundamentals of detection and estimation for signal processing, communications, and control. Topics covered include: vector spaces of random variables; Bayesian and Neyman-Pearson hypothesis testing; Bayesian and nonrandom parameter estimation; minimum-variance unbiased estimators and the Cramer-Rao bounds; representations for stochastic processes, shaping and whitening filters, and Karhunen-Loeve expansions; and detection and estimation from waveform observations. Advanced topics include: linear prediction and spectral estimation, and Wiener and Kalman filters. This course examines the fundamentals of detection and estimation for signal processing, communications, and control. Topics covered include: vector spaces of random variables; Bayesian and Neyman-Pearson hypothesis testing; Bayesian and nonrandom parameter estimation; minimum-variance unbiased estimators and the Cramer-Rao bounds; representations for stochastic processes, shaping and whitening filters, and Karhunen-Loeve expansions; and detection and estimation from waveform observations. Advanced topics include: linear prediction and spectral estimation, and Wiener and Kalman filters.Subjects

stochastic process | stochastic process | detection | detection | estimation | estimation | signal processing | signal processing | communications | communications | control | control | vector spaces | vector spaces | Bayesian | Bayesian | Neyman-Pearson | Neyman-Pearson | minimum-variance unbiased estimator | minimum-variance unbiased estimator | Cramer-Rao bounds | Cramer-Rao bounds | shaping filter | shaping filter | whitening filter | whitening filter | Karhunen-Loeve expansion | Karhunen-Loeve expansion | waveform observation | waveform observation | linear prediction | linear prediction | spectral estimation | spectral estimation | Wiener filter | Wiener filter | Kalman filter | Kalman filterLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata17.267 Democracy in America (MIT) 17.267 Democracy in America (MIT)

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This course examines the functioning of democracy in the U.S. beginning with the theoretical foundations of democratic representation. It explores how the views of the public influence policy making. It also examines factors, such as malapportionment, that lead to non-majoritarian outcomes. Evidence on how well policy outcomes reflect public opinion is reviewed, and whether certain groups are over or under-represented in the policy process. Also discussed are reforms that might make our democracy more responsive to the American public. This course examines the functioning of democracy in the U.S. beginning with the theoretical foundations of democratic representation. It explores how the views of the public influence policy making. It also examines factors, such as malapportionment, that lead to non-majoritarian outcomes. Evidence on how well policy outcomes reflect public opinion is reviewed, and whether certain groups are over or under-represented in the policy process. Also discussed are reforms that might make our democracy more responsive to the American public.Subjects

democratic representation | democratic representation | public opinion | public opinion | malapportionment | malapportionment | institutional reform | institutional reform | non-majoritarian policy | non-majoritarian policy | meidan voter | meidan voter | electoral accountability | electoral accountability | primary constituencies | primary constituencies | elites | elites | voter turnout | voter turnout | interest groups | interest groups | incumbency bias | incumbency bias | one-person | one-vote | one-person | one-vote | term limits | term limits | udges | udges | redistricting | redistricting | campaign finance | campaign finance | convenience voting | convenience votingLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.63J System Safety (MIT) 16.63J System Safety (MIT)

Description

This class introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems. This class introduces the concepts of system safety and how to analyze and design safer systems. Topics include the causes of accidents in general, and recent major accidents in particular; hazard analysis, safety-driven design techniques; design of human-automation interaction; integrating safety into the system engineering process; and managing and operating safety-critical systems.Subjects

16.63 | 16.63 | ESD.03 | ESD.03 | hazard analysis | hazard analysis | system safety | system safety | accident analysis | accident analysis | design for safety | design for safety | accident causality mode | accident causality mode | hindsight bias | hindsight bias | accident report | accident report | occupational safety | occupational safety | CAST analysis | CAST analysis | human factors | human factors | safety control structure | safety control structure | operations | operations | safety management | safety management | critical projects | critical projects | STPA hazard analysis | STPA hazard analysis | STAMP | STAMPLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata16.863J System Safety (MIT) 16.863J System Safety (MIT)

Description

The goal of 16.863J is to teach basic principles of system safety, including accident analysis, hazard analysis, design for safety, human factors and safety, controlling safety during operations, and management of safety critical projects and systems. While you will learn what is currently done today, you will also learn new techniques that are proving to be more powerful and effective than the traditional safety engineering approaches. The goal of 16.863J is to teach basic principles of system safety, including accident analysis, hazard analysis, design for safety, human factors and safety, controlling safety during operations, and management of safety critical projects and systems. While you will learn what is currently done today, you will also learn new techniques that are proving to be more powerful and effective than the traditional safety engineering approaches.Subjects

16.863 | 16.863 | ESD.863 | ESD.863 | hazard analysis | hazard analysis | system safety | system safety | accident analysis | accident analysis | design for safety | design for safety | accident causality mode | accident causality mode | hindsight bias | hindsight bias | accident report | accident report | occupational safety | occupational safety | CAST analysis | CAST analysis | human factors | human factors | safety control structure | safety control structure | operations | operations | safety management | safety management | critical projects | critical projects | STPA hazard analysis | STPA hazard analysisLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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