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"Picking up where the original Against All Odds left off in the 1980s, the new series maintains the same emphasis on "doing" statistics. Video modules take viewers on location to where people from all walks of life are using statistics in their work. Online materials allow viewers to practice and review what they’ve learned." -- Annenberg Learner
"SDA is a set of programs for the documentation and Web-based analysis of survey data. SDA was developed, distributed and supported by the Computer-assisted Survey Methods Program (CSM) at the University of California, Berkeley until the end of 2014. Beginning in 2015, CSM is managed and supported by the Institute for Scientific Analysis, a private, non-profit organization, under an exclusive continuing license agreement with the University of California."--website
From the developer website: "Wolfram|Alpha App lets you instantly compute answers to questions across thousands of domains—from finance and food to math and medicine to stocks and spacecraft to wordplay and weather..."
MITOPENCOURSEWARE This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.
MITOPENCOURSEWARE The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management. This resource is a companion site to 6.041SC Probabilistic Systems Analysis and Applied Probability. It covers the same content, using videos developed for an edX version of the course.
"R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues...R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.."