Courses tagged with "Nutrition" (6413)

This course introduces the basic ideas and equations of Einstein's Special Theory of Relativity. If you have hoped to understand the physics of Lorentz contraction, time dilation, the "twin paradox", and E=mc², you're in the right place.

Acknowledgements

Prof. Knuteson wishes to acknowledge that this course was originally designed and taught by Prof. Robert Jaffe.

Offered in the spring and fall terms, Introduction to Stagecraft is a hands-on course that gets students working with the tools and techniques of theatrical production in a practical way. It is not a design course but one devoted to artisanship. Among the many remarkable final projects that have been proposed and presented at the end of the course have been a Renaissance hourglass blown in the MIT glass shop and set into a frame turned on our set shop lathe; a four harness loom built by a student who then wove cloth on it; a number of chain mail tunics and coifs; a wide variety of costume and furniture pieces and electrified period lighting fixtures.

The "sense-and-correct" nature of feedback controllers make them an appealing choice for systems whose actuators, or environments, are highly variable. If the system also requires high performance (e.g. an industrial robot, a car, or an aircraft), the usual approach is to use a state-space feedback controller derived from a physics-based model. And when performance is less critical (e.g. for toys and appliances), the traditional choice has been to tune a low-cost proportional-derivative-integral (PID) controller.

Over the last few years, much has changed. The dramatic decline in the cost of accurate sensors and fast microcontrollers have made state-space controllers practical even for inexpensive toys. In addition, modeling approaches have become far more reliant on measurement and computation rather than physics and analysis. In this course, we examine the theory and application of this arc of alternatives to control, starting with PID, then moving to physical-modeling and state-space, and ending with state-space using measurement-based modeling. In each case, you will design and test controllers with your own copter-levitated arm, to solidify your understanding and to gain insight in to the practical issues.

PLEASE NOTE: This is intended to be an advanced course and students should have a background in linear algebra and differential equations, as well as some experience with control systems. IN ADDITION: THIS IS A BETA COURSE, THINGS WILL GO WRONG. We are testing a new type of on-line class, one where students use advanced concepts to design and then examine performance results on their own hardware. There will be difficulties, and we will be updating content and focus in response to student input.

This data course is a primer to statistical genetics and covers an approach called linkage disequilibrium mapping, which analyzes non-familial data and has been successfully used to identify genetic variants associated with common and complex genetic traits.

We hope many students find this introductory course interesting and are motivated to study further topics in statistical genetics to understand biological variation from statistical standpoints.

Previous knowledge of molecular genetics and basic statistical concepts, such as statistical tests and estimation, is required. Basic knowledge on genetic variations is offered at the start of the course.

This course will provide a solid foundation in probability and statistics for economists and other social scientists. We will emphasize topics needed for further study of econometrics and provide basic preparation for 14.32. Topics include elements of probability theory, sampling theory, statistical estimation, and hypothesis testing.

This course exposes students to the logic of statistical reasoning and its application in the quantitative social sciences. It is meant as a thorough but accessible introduction to the topics of descriptive statistics, probability theory, and statistical inference with hands-on exercises.

We are surrounded by information, much of it numerical, and it is important to know how to make sense of it. Stat2x is an introduction to the fundamental concepts and methods of statistics, the science of drawing conclusions from data.

The course is the online equivalent of Statistics 2, a 15-week introductory course taken in Berkeley by about 1,000 students each year. Stat2x is divided into three 5-week components. Stat2.1x is the first of the three.

The focus of Stat2.1x is on descriptive statistics. The goal of descriptive statistics is to summarize and present numerical information in a manner that is illuminating and useful. The course will cover graphical as well as numerical summaries of data, starting with a single variable and progressing to the relation between two variables. Methods will be illustrated with data from a variety of areas in the sciences and humanities.

There will be no mindless memorization of formulas and methods. Throughout Stat2.1x, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

FAQ

• What is the format of the class?
  • Instruction will be consist of brief lectures and exercises to check comprehension. Grades (Pass or Not Pass) will be decided based on a combination of scores on short assignments, quizzes, and a final exam.
• How much does it cost to take the course?
  • Nothing! The course is free.
• Will the text of the lectures be available?
  • Yes. All of our lectures will have transcripts synced to the videos.
• Do I need to watch the lectures live?
  • No. You can watch the lectures at your leisure.
• Can I contact the Instructor or Teaching Assistants?
  • Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.
• Do I need any other materials to take the course?
  • If you have any questions about edX generally, please see the edX FAQ.

Statistics 2 at Berkeley is an introductory class taken by about 1,000 students each year. Stat2.3x is the last in a sequence of three courses that make up Stat2x, the online equivalent of Berkeley's Stat 2. The focus of Stat2.3x is on statistical inference: how to make valid conclusions based on data from random samples. At the heart of the main problem addressed by the course will be a population (which you can imagine for now as a set of people) connected with which there is a numerical quantity of interest (which you can imagine for now as the average number of MOOCs the people have taken). If you could talk to each member of the population, you could calculate that number exactly. But what if the population is so large that your resources will not stretch to interviewing every member? What if you can only reach a subset of the population?

Stat 2.3x will discuss good ways to select the subset (yes, at random); how to estimate the numerical quantity of interest, based on what you see in your sample; and ways to test hypotheses about numerical or probabilistic aspects of the problem.

The methods that will be covered are among the most commonly used of all statistical techniques. If you have ever read an article that claimed, "The margin of error in such surveys is about three percentage points," or, "Researchers at the University of California at Berkeley have discovered a highly significant link between ...," then you should expect that by the end of Stat 2.3x you will have a pretty good idea of what that means. Examples will range all the way from a little girl's school science project (seriously – she did a great job and her results were published in a major journal) to rulings by the U.S. Supreme Court.

The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

Statistics 2 at Berkeley is an introductory class taken by about 1000 students each year. Stat2.2x is the second of three five-week courses that make up Stat2x, the online equivalent of Berkeley's Stat 2.

The focus of Stat2.2x is on probability theory: exactly what is a random sample, and how does randomness work? If you buy 10 lottery tickets instead of 1, does your chance of winning go up by a factor of 10? What is the law of averages? How can polls make accurate predictions based on data from small fractions of the population? What should you expect to happen "just by chance"? These are some of the questions we will address in the course.

We will start with exact calculations of chances when the experiments are small enough that exact calculations are feasible and interesting. Then we will step back from all the details and try to identify features of large random samples that will help us approximate probabilities that are hard to compute exactly. We will study sums and averages of large random samples, discuss the factors that affect their accuracy, and use the normal approximation for their probability distributions.

Be warned: by the end of Stat2.2x you will not want to gamble. Ever. (Unless you're really good at counting cards, in which case you could try blackjack, but perhaps after taking all these edX courses you'll find other ways of earning money.)

The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

FAQ

• What is the format of the class?
  • Instruction will be consist of brief lectures and exercises to check comprehension. Grades (Pass or Not Pass) will be decided based on a combination of scores on short assignments, quizzes, and a final exam.
• How much does it cost to take the course?
  • Nothing! The course is free.
• Will the text of the lectures be available?
  • Yes. All of our lectures will have transcripts synced to the videos.
• Do I need to watch the lectures live?
  • No. You can watch the lectures at your leisure.
• Will certificates be awarded?
  • Yes. Online learners who achieve a passing grade in a course can earn a certificate of achievement. These certificates will indicate you have successfully completed the course, but will not include a specific grade. Certificates will be issued by edX under the name of BerkeleyX, designating the institution from which the course originated.
• Can I contact the Instructor or Teaching Assistants?
  • Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.
• Do I need any other materials to take the course?
  • If you have any questions about edX generally, please see the edX FAQ.

This course is an introduction to steel, exploring its history and cultural context, where it comes from, how it works, why we use so much of it, and how we might use it in the future.

It is delivered in a lively manner using everyday examples, demonstrations, and film footage of steel making. 

This course is an introduction to Markov chains, random walks, martingales, and Galton-Watsom tree. The course requires basic knowledge in probability theory and linear algebra including conditional expectation and matrix.

This is a short interdisciplinary course on strategic thinking and some of its most powerful tools. Strategic thinking is not exclusive to business or military applications. The skills taught in this course can be used by everyone.

This course introduces the academic discipline of sustainability and explores how today’s human societies can endure in the face of global change, ecosystem degradation and resource limitations.

This class assesses current and potential future energy systems, covering resources, extraction, conversion, and end-use technologies, with emphasis on meeting regional and global energy needs in the 21st century in a sustainable manner. Instructors and guest lecturers will examine various renewable and conventional energy production technologies, energy end-use practices and alternatives, and consumption practices in different countries. Students will learn a quantitative framework to aid in evaluation and analysis of energy technology system proposals in the context of engineering, political, social, economic, and environmental goals. Students taking the graduate version, Sustainable Energy, complete additional assignments.

This class assesses current and potential future energy systems, covering resources, extraction, conversion, and end-use technologies, with emphasis on meeting regional and global energy needs in the 21st century in a sustainable manner. Instructors and guest lecturers will examine various renewable and conventional energy production technologies, energy end-use practices and alternatives, and consumption practices in different countries. Students will learn a quantitative framework to aid in evaluation and analysis of energy technology system proposals in the context of engineering, political, social, economic, and environmental goals. Students taking the graduate version, Sustainable Energy, complete additional assignments.

This class assesses current and potential future energy systems, covering resources, extraction, conversion, and end-use technologies, with emphasis on meeting regional and global energy needs in the 21st century in a sustainable manner. Instructors and guest lecturers will examine various renewable and conventional energy production technologies, energy end-use practices and alternatives, and consumption practices in different countries. Students will learn a quantitative framework to aid in evaluation and analysis of energy technology system proposals in the context of engineering, political, social, economic, and environmental goals. Students taking the graduate version, Sustainable Energy, complete additional assignments.

This course is concerned with the concepts and principles which have been of central significance in the recent development of syntactic theory, with special focus on the "Government and Binding" (GB) / "Principles and Parameters" (P&P) / "Minimalist Program" (MP) approach.

It is the first of a series of two courses (24.951 is taught during the Fall and 24.952 is taught in the Spring). This course deals mostly with phrase structure, argument structure and its syntactic expression, including "A-movement". Though other issues (e.g. wh-movement, antecedent-contained deletion, extraposition) may be mentioned during the semester, the course will not systematically investigate these topics in class until 24.952.

The goal of the course is to understand why certain problems have been treated in certain ways. Thus, on many occasions a variety of approaches will be discussed, and the (recent) historical development of these approaches are emphasized.

Introduction to systems thinking and system dynamics modeling applied to strategy, organizational change, and policy design. Students use simulation models, management flight simulators, and case studies to develop conceptual and modeling skills for the design and management of high-performance organizations in a dynamic world.

This course is about learning to program well: building programs that are elegant, well tested and easy to maintain. The course is designed for students with no programming experience at all. Nonetheless, former students who already knew how to program have said it made them better programmers.

Learn to assess data from clinical trials by performing systematic reviews and meta-analyses.