Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers of degrees of freedom. In this two-semester course, basic principles are examined. Topics include: thermodynamics, probability theory, kinetic theory, classical statistical mechanics, interacting systems, quantum statistical mechanics, and identical particles.

This course discusses the principles and methods of statistical mechanics. Topics covered include classical and quantum statistics, grand ensembles, fluctuations, molecular distribution functions, other concepts in equilibrium statistical mechanics, and topics in thermodynamics and statistical mechanics of irreversible processes.

Statistical Physics in Biology is a survey of problems at the interface of statistical physics and modern biology. Topics include: bioinformatic methods for extracting information content of DNA; gene finding, sequence comparison, and phylogenetic trees; physical interactions responsible for structure of biopolymers; DNA double helix, secondary structure of RNA, and elements of protein folding; considerations of force, motion, and packaging; protein motors, membranes. We also look at collective behavior of biological elements, cellular networks, neural networks, and evolution.

This course provides an introduction to the physical chemistry of biological systems. Topics include: connection of macroscopic thermodynamic properties to microscopic molecular properties using statistical mechanics, chemical potentials, equilibrium states, binding cooperativity, behavior of macromolecules in solution and at interfaces, and solvation. Example problems include protein structure, genomic analysis, single molecule biomechanics, and biomaterials.

This course explores the theory of self-assembly in surfactant-water (micellar) and surfactant-water-oil (micro-emulsion) systems. It also introduces the theory of polymer solutions, as well as scattering techniques, light, x-ray, and neutron scattering applied to studies of the structure and dynamics of complex liquids, and modern theory of the liquid state relevant to structured (supramolecular) liquids.

This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.

A whirl-wind tour of the statistics used in behavioral science research, covering topics including: data visualization, building your own null-hypothesis distribution through permutation, useful parametric distributions, the generalized linear model, and model-based analyses more generally. Familiarity with MATLABA, Octave, or R will be useful, prior experience with statistics will be helpful but is not essential. This course is intended to be a ground-up sketch of a coherent, alternative perspective to the "null-hypothesis significance testing" method for behavioral research (but don't worry if you don't know what this means).

This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics.

Have you ever considered going to a pharmacy to order some new cardiomyocytes (heart muscle cells) for your ailing heart? It might sound crazy, but recent developments in stem cell science have made this concept not so futuristic. In this course, we will explore the underlying biology behind the idea of using stem cells to treat disease, specifically analyzing the mechanisms that enable a single genome to encode multiple cell states ranging from neurons to fibroblasts to T cells. Overall, we hope to provide a comprehensive overview of this exciting new field of research and its clinical relevance. 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. Many instructors of the Advanced Undergraduate Seminars are postdoctoral scientists with a strong interest in teaching.

Estimation and control of dynamic systems. Brief review of probability and random variables. Classical and state-space descriptions of random processes and their propagation through linear systems. Frequency domain design of filters and compensators. The Kalman filter to estimate the states of dynamic systems. Conditions for stability of the filter equations.

Fundamentals of detection and estimation for signal processing, communications, and control. 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; Karhunen-Loeve expansions. Detection and estimation from waveform observations. Advanced topics: linear prediction and spectral estimation; Wiener and Kalman filters.

The transition from high school and home to college and a new living environment can be a fascinating and interesting time, made all the more challenging and interesting by being at MIT. More than recording the first semester through a series of snapshots, this freshman seminar will attempt to teach photography as a method of seeing and a tool for better understanding new surroundings. Over the course of the semester, students will develop a body of work through a series of assignments, and then attempt to describe the conditions and emotions of their new environment in a cohesive final presentation.

12.103 explores the role of scientific knowledge, discovery, method, and argument in environmental policymaking from both idealistic and realistic perspectives. The course will use case studies of science-intensive environmental controversies to study how science was used and abused in the policymaking process. Case studies include: global warming, biodiversity loss, and nuclear waste disposal siting. Subject includes intensive practice in the writing and presentation of "position statements" on environmental science issues.

Design and execution of human resource management strategies. Two central themes: (1) How to think systematically and strategically about aspects of managing the organization's human assets, and (2) What really needs to be done to implement these policies and to achieve competitive advantage. Adopts the perspective of a general manager and addresses human resource topics (including reward systems, performance management, high-performance human resource systems, training and development, recruitment, retention, equal employment opportunity laws, work-force diversity, and union-management relationships) from a strategic perspective.

Subject focuses on some of the important current issues in strategic management. It concentrates on modern analytical approaches and on enduring successful strategic practices. It is consciously designed with a technological and global outlook since this orientation in many ways highlights the significant emerging trends in strategic management. Subject is intended to provide the students with a pragmatic approach that guides the formulation and implementation of corporate, business, and functional strategies. Restricted to Sloan Fellows.

This course is intended to be an extension of course 15.902, Strategic Management, with the purpose of allowing the students to experience an in-depth application of the concepts and frameworks of strategic management. Throughout the course, Professor Hax will discuss the appropriate methodologies, concepts, and tools pertinent to strategic analyses and will illustrate their use by discussing many applications in real-life settings, drawn from his own personal experiences.

Examines the fundamental concepts of strategic planning and management in the context of the real estate, design, and construction industry. Discusses the basic business relationships among firms in the design and construction value chain. Specific topics include: industry analysis; strategic planning models; information technology strategy; strategy in fragmented industries; negotiation; and macro trends shaping the industry as a whole. Case method of instruction is used, and supplemented by extensive readings. From the course home page: This course provides an overview of key concepts in strategic management in the construction, real estate, and architecture industries. Topics include supply chain analysis, market segmentation, vertical integration, competitive advantage, and industry transformation. This course is of interest to students seeking more understanding of the business dynamics of real estate and construction; seeking to provide value in firms which they may join; or seeking to build a foundation for their own entrepreneurial pursuits.

A project subject that teaches students how to create, carry out, interpret, and analyze a market research questionnaire. Emphasis on discovering market structure and segmentation, but students can pursue other project applications. Includes a user-oriented treatment of multivariate analysis (factor analysis, multidimensional scaling, conjoint and cluster analysis).

Strategic Organizational Design focuses on effective organizational design in both traditional and innovative organizations, with special emphasis on innovative organizational forms that can provide strategic advantage. Topics include when to use functional, divisional, or matrix organizations, how IT creates new organizational possibilities, and examples of innovative organizational possibilities, such as democratic decision-making, crowd-based organizations, internal resource markets, and other forms of collective intelligence. Team projects include inventing new possibilities for real organizations.

This course teaches the art of guessing results and solving problems without doing a proof or an exact calculation. Techniques include extreme-cases reasoning, dimensional analysis, successive approximation, discretization, generalization, and pictorial analysis. Applications include mental calculation, solid geometry, musical intervals, logarithms, integration, infinite series, solitaire, and differential equations. (No epsilons or deltas are harmed by taking this course.) This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.