In this lesson, students investigate these questions by analyzing videos of dancing through the decades. With the help of a worksheet, student groups watch footage of the Charleston and Lindy Hop, the Mambo, "Love-in" dancing, Disco, and Break Dancing. Based on their informed observation of these styles, they then debate whether dance has "evolved" in American culture, or remained mostly the same.

Taking Sam Phillips as a case study, this lesson explores the role of the producer in the recording studio as one defined by an ability to guide the recording process but also to affect the wider cultural context. After investigating what a producer does and why an artist might benefit from a producer's services, this lesson looks at the way Sam Phillips' approach in some ways reflects the trend of urbanization in the American South. Like Phillips, many of his artists came from rural backgrounds and were seeking the benefits of urban life. That move toward the urban, and the racial mixing it fostered, was almost encoded in the music, as the lesson activities will illuminate. Finally, the lesson looks at Phillip's guidance of a young Elvis Presley and suggests how the music they produced created an opening for African-American music to "crossover" into mainstream American popular music.

Phil Spector and George Martin both created defining sounds of the 1960s, but, inevitably, as music and culture changed, so too did some musicians' ideas about allowing producers to exert control over their music. Some of the Singer-Songwriters of the early 1970s, such as Joni Mitchell, accepted little or no input from producers, focusing on the clarity and directness of the lyrics with sometimes minimal musical accompaniment. In the latter part of this lesson, students use a handout with information about both Betty Friedan's seminal The Feminine Mystique and events in 1960s Second-Wave Feminism as a backdrop by which to consider Joni Mitchell's decision to "self-produce"in the early 1970s.

To many, the sense of limitless possibility The Beatles arrived at while working inside Abbey Road Studios was part of a broader pattern of change connected to the 1960s countercultural movement. Political and social events, including student protests against the Vietnam War, a popular interest in the study of Eastern religions, and the publication of books such as 1964's The Psychedelic Experience, helped to inform The Beatles' musical decisions as much as the music the group invented fueled the rise of a new youth culture. The Beatles provided the soundtrack to a new experience. As popular icons that challenged social norms and encouraged creative thinking, recording artists like The Beatles began using multitracking technology to make music in the studio that could not be reproduced on the concert stage and that expanded our understanding of what popular music could be and what it could do. The studio was no longer a predictable space for recording live performances; it became a laboratory for constructing sophisticated musical imaginings. As such, it was a perfect reflection of the new youth culture's spirit.

This course teaches critical learning abilities that are skills and attitudes to be taught across the curriculum: communication, problem solving or critical thinking, responsibility, and global awareness or diversity/appreciation. To these, we add information/technology literacy, and lifelong learning. By the end of the course students will be able to: Identify the major political, economic, and social developments in Pacific Northwest history and especially in the state of Washington; Integrate the perspectives of different peoples to interpret Pacific Northwest history; Describe the Pacific Northwestęs role in the context of American and world history; Apply your knowledge of Pacific Northwest history to your life by conducting an oral history and by researching and writing about issues in the region today; and Define current environmental issues in the Pacific Northwest and analyze their historical context.

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.

Physical Geography, also called earth science, is the study of our home planet and all of its components: its lands, waters, atmosphere, and interior. In this book, some chapters are devoted to the processes that shape the lands and impact people. Other chapters depict the processes of the atmosphere and its relationship to the planet’s surface and all our living creatures. For as long as people have been on the planet, humans have had to live within Earth’s boundaries. Now human life is having a profound effect on the planet. Several chapters are devoted to the effect people have on the planet.The journey to better understanding Earth begins here with an exploration of how scientists learn about the natural world and introduces you to the study of physical geography and earth science.

SP.255 is a lecture, discussion, and project based seminar about the physics of rock climbing. Participants are first exposed to the unsolved problems in the climbing community that could be answered by research and then asked to solve a small part of one of these problems. The seminar provides an introduction to engineering problems, an opportunity to practice communication skills, and a brief stab at doing some research. This seminar explicitly does not include climbing instruction nor is climbing/mountaineering experience a prerequisite.

Examines the history of the United States as a "nation of immigrants" within a broader global context. Considers migration from the mid-19th century to the present through case studies of such places as New York's Lower East Side, South Texas, Florida, and San Francisco's Chinatown. Examines the role of memory, media, and popular culture in shaping ideas about migration. Includes optional field trip to New York City.

This course takes a broad-based look at poker theory and applications of poker analytics to investment management and trading.

Precalculus 1 & 2 / Trigonometry provides a study of functions and their graphs, including polynomial, rational, exponential, and logarithmic functions. Additionally, right-triangle trigonometry, trigonometric functions and their applications are covered.

This course will cover families of trigonometric functions, their inverses, properties, graphs, and applications. Additionally we will study trigonometric equations and identities, the laws of sines and cosines, polar coordinates and graphs, parametric equations and elementary vector operations.Login: guest_oclPassword: ocl

This course will cover families of functions, their properties, graphs and applications. These functions include: polynomial, rational, exponential, logarithmic functions and combinations of these. We will solve related equations and inequalities and conduct data analysis, introductory mathematical modeling and develop competency with a graphing calculator.Login: guest_oclPassword: ocl

Prediction is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning and statistics, and more generally, data mining. Machine learning and statistical methods are used throughout the scientific world for their use in handling the "information overload" that characterizes our current digital age. Machine learning developed from the artificial intelligence community, mainly within the last 30 years, at the same time that statistics has made major advances due to the availability of modern computing. However, parts of these two fields aim at the same goal, that is, of prediction from data. This course provides a selection of the most important topics from both of these subjects.

This course is organized around the well-established planning, organizing, leading, and controlling framework (or, simply, P-O-L-C). Three underlying themes carry throughout: strategic thinking, entrepreneurial thinking, and active management.

Marketing is a tool used by companies, organizations, and people to shape our perceptions and persuade us to change our behavior. The most effective marketing uses a well-designed strategy and a variety of techniques to alter how people think about and interact with the object in question. Less-effective marketing causes people to turn off, tune out, or not even notice. Why should you care about marketing? Marketing is an ever-present force in modern society, and it can work amazingly well to influence what we do and why we do it.

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.

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.