In this lesson students will see the different types of evidence scientists use to understand evolutionary relationships among organisms. They will first practice by using shared physical characteristics to predict relationships among members of the cat family and then use this approach to predict primate relationships. They will compare their predictions to evidence provided by analyzing amino acid sequences and build a phylogenetic tree based on these sequences. Finally, they will look at the tree in the context of time in order to see divergence times.

This Protein Purification video lesson is intended to give students some insight into the process and tools that scientists and engineers use to explore proteins. It is designed to extend the knowledge of students who are already somewhat sophisticated and who have a good understanding of basic biology. The question that motivates this lesson is, ''what makes two cell types different?'' and this question is posed in several ways. Such scientific reasoning raises the experimental question: how could you study just a subset of specialized proteins that distinguish one cell type from another? Two techniques useful in this regard are considered in the lesson.

Hitherto it had gone by the original Indian name Manna-hatta, or as some still have it, 'The Manhattoes'; but this was now decried as savage and heathenish... At length, when the council was almost in despair, a burgher, remarkable for the size and squareness of his head, proposed that they should call it New-Amsterdam. The proposition took every body by surprise; it was so striking, so apposite, so ingenious. The name was adopted by acclamation, and New-Amsterdam the metropolis was thenceforth called. --Washington Irving, 1808 In less tongue-in-cheek style, this course examines the evolution of New York City from 1607 to the present. The readings focus on the city's social and physical histories, and the class discussions compare New York's development to patterns in other cities.

This half-semester course provides an introduction to microeconomic theory designed to meet the needs of students in an 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. Students should be comfortable with multivariable calculus, linear algebra, and basic real analysis.

This course offers an introduction to noncooperative game theory. The course is intended both for graduate students who wish to develop a solid background in game theory in order to pursue research in the applied fields of economics and related disciplines, and for students wishing to specialize is economic theory. While the course is designed for graduate students in economics, it is open to all students who have taken and passed 14.121. The recommended primary text for the course is Drew Fudenberg and Jean Tirole's text, Game Theory. The text covers all the material in the course and much more, but has less in the way of intuition and examples than some students would like. For this reason, students might alternately wish to use Robert Gibbons' Game Theory for Applied Economists as their primary reference. Gibbons' book contains more readable discussions of the material and a lot of nice examples, but omits a few of the topics we'll cover. The course will be graded on the basis of five problem sets and a three hour final exam. In order to learn the material it is absolutely essential to do the problem sets. The problem sets will count for approximately one-fourth of the course grade.

This is a half-semester course which covers the topics in Microeconomic Theory that everybody with a Ph.D. from MIT Economics Department should know but that have not yet been covered in the Micro sequence. Hence, it covers several unrelated topics. The topics come from three general areas: Decision Theory, Game Theory, and Behaviorla Economics.  I will try my best to put them in a coherent narrative, but there will be inherent jumps from topic to topic.

Microeconomics will ground you in - surprise - basic microeconomics-how markets function, how to think about allocating scarce resources among competing uses, what profit maximizing behavior means in industries with different numbers of competitors, how technology and trade reshapes the opportunities people face, and so on. We will apply economic ideas to understand current economic problems, including the housing bubble, the current unemployment situation (particularly for high school gradutes), how Google makes its money and why healthcare costs are rising so fast.

" 6.012 is the header course for the department's "Devices, Circuits and Systems" concentration. The topics covered include modeling of microelectronic devices, basic microelectronic circuit analysis and design, physical electronics of semiconductor junction and MOS devices, relation of electrical behavior to internal physical processes, development of circuit models, and understanding the uses and limitations of various models. The course uses incremental and large-signal techniques to analyze and design bipolar and field effect transistor circuits, with examples chosen from digital circuits, single-ended and differential linear amplifiers, and other integrated circuits."

" 6.012 is the header course for the department's "Devices, Circuits and Systems" concentration. The topics covered include: modeling of microelectronic devices, basic microelectronic circuit analysis and design, physical electronics of semiconductor junction and metal-on-silicon (MOS) devices, relation of electrical behavior to internal physical processes, development of circuit models, and understanding the uses and limitations of various models. The course uses incremental and large-signal techniques to analyze and design bipolar and field effect transistor circuits, with examples chosen from digital circuits, single-ended and differential linear amplifiers, and other integrated circuits."

This course surveys the history of the Middle East, from the end of the 19th century to the present. It examines major political, social, intellectual and cultural issues and practices. It also focuses on important events, movements, and ideas that prevailed during the last century and affect its current realities.

This course is an introduction to many of the central issues in a branch of philosophy called philosophy of mind.

Modal logic is the logic of necessity and possibility, and by extension of analogously paired notions like validity and consistency, obligation and permission, the known and the not-ruled-out. This a first course in the area. A solid background in first-order logic is essential. Topics to be covered include (some or all of) the main systems of propositional modal logic, Kripkean "possible world" semantics, strict implication, contingent identity, intensional objects, counterpart theory, the logic of actuality, and deontic and / or epistemic logic. The emphasis will be more on technical methods and results than philosophical applications.

Second subject of two-term sequence on modeling, analysis and control of dynamic systems. Kinematics and dynamics of mechanical systems including rigid bodies in plane motion. Linear and angular momentum principles. Impact and collision problems. Linearization about equilibrium. Free and forced vibrations. Sensors and actuators. Control of mechanical systems. Integral and derivative action, lead and lag compensators. Root-locus design methods. Frequency-domain design methods. Applications to case-studies of multi-domain systems.

First of two-term sequence on modeling, analysis and control of dynamic systems. Mechanical translation, uniaxial rotation, electrical circuits and their coupling via levers, gears and electro-mechanical devices. Analytical and computational solution of linear differential equations and state-determined systems. Laplace transforms, transfer functions. Frequency response, Bode plots. Vibrations, modal analysis. Open- and closed-loop control, instability. Time-domain controller design, introduction to frequency-domain control design techniques. Case studies of engineering applications.

This course provides an introduction to the study of environmental phenomena that exhibit both organized structure and wide variability - i.e., complexity. Through focused study of a variety of physical, biological, and chemical problems in conjunction with theoretical models, we learn a series of lessons with wide applicability to understanding the structure and organization of the natural world. Students will also learn how to construct minimal mathematical, physical, and computational models that provide informative answers to precise questions.

Explores the theory and practice of scientific modeling in the context of auditory and speech biophysics. Based principally on seminar-style discussions of the research literature, subject draws on examples from hearing and speech (e.g., cochlear and vocal-fold mechanics) to explore general, meta-theoretical issues that transcend the particular subject matter. Examples include: What is a model? What is the process of model building? What are the different approaches to modeling? What is the relationship between theory and experiment? How are models tested? What constitutes a good model?

Mathematical modeling of complex engineering systems at a level of detail compatible with the design and implementation of modern control systems. Wave-like and diffusive energy transmission systems. Multiport energy storing fields and dissipative fields; consequences of symmetry and asymmetry. Nonlinear mechanics and canonical transformation theory. Examples will include mechanisms, electromechanical transducers, electronic systems, fluid systems, thermal systems, compressible flow processes, chemical processes. This course models multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms; nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms; and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission.

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.

This undergraduate course focuses on traditional algebra topics that have found greatest application in science and engineering as well as in mathematics.

This class provides an introduction to modern art and theories of modernism and postmodernism. It focuses on the way artists use the tension between fine art and mass culture to mobilize a critique of both. We will examine objects of visual art, including painting, sculpture, architecture, photography, prints, performance and video. These objects will be viewed in their interaction with advertising, caricature, comics, graffiti, television, fashion, folk art, and "primitive" art.