Forecasting: principles and practice This is the second edition of Forecasting: Principles & Practice, which uses the forecast package in R. The third edition, which uses the fable package, is also available. Welcome to our online textbook on forecasting. This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. The book is written for three audiences: (1) people finding themselves doing forecasting in business when they may not have had any formal training in the area; (2) undergraduate students studying business; (3) MBA students doing a forecasting elective. For most sections, we only assume that readers are familiar with introductory statistics, and with high-school algebra. At the end of each chapter we provide a list of “further reading”. We use R throughout the book and we intend students to learn how to forecast with R. We will use the ggplot2 package for all graphics. Happy forecasting!
Machine Learning Repository Interactive Statistical Calculation Pages Debunking Handbook, The Posted on 27 November 2011 by John Cook The Debunking Handbook, a guide to debunking misinformation, is now freely available to download. Although there is a great deal of psychological research on misinformation, there's no summary of the literature that offers practical guidelines on the most effective ways of reducing the influence of myths. The Debunking Handbook boils the research down into a short, simple summary, intended as a guide for communicators in all areas (not just climate) who encounter misinformation. The Handbook explores the surprising fact that debunking myths can sometimes reinforce the myth in peoples' minds. Communicators need to be aware of the various backfire effects and how to avoid them, such as: It also looks at a key element to successful debunking: providing an alternative explanation. The Authors: John Cook is the Climate Change Communication Fellow for the Global Change Institute at the University of Queensland. Update: Translations
CS 229: Machine Learning (Course handouts) Lecture notes 1 (ps) (pdf) Supervised Learning, Discriminative Algorithms Lecture notes 2 (ps) (pdf) Generative Algorithms Lecture notes 3 (ps) (pdf) Support Vector Machines Lecture notes 4 (ps) (pdf) Learning Theory Lecture notes 5 (ps) (pdf) Regularization and Model Selection Lecture notes 6 (ps) (pdf) Online Learning and the Perceptron Algorithm. (optional reading) Lecture notes 7a (ps) (pdf) Unsupervised Learning, k-means clustering. Lecture notes 7b (ps) (pdf) Mixture of Gaussians Lecture notes 8 (ps) (pdf) The EM Algorithm Lecture notes 9 (ps) (pdf) Factor Analysis Lecture notes 10 (ps) (pdf) Principal Components Analysis Lecture notes 11 (ps) (pdf) Independent Components Analysis Lecture notes 12 (ps) (pdf) Reinforcement Learning and Control Supplemental notes 1 (pdf) Binary classification with +/-1 labels. Supplemental notes 2 (pdf) Boosting algorithms and weak learning.
Resources for Statistical Computing Other Resources for Help with Statistical Computing The primary mission of the IDRE Statistical Consulting Group is to support UCLA researchers in statistical computing using statistical packages like SAS, Stata, SPSS, HLM, MLwiN, Mplus and so forth. We provide this support through our web pages, our walk in consulting services, classes and seminars, and email consulting. Below, we provide a list of commonly used statistical software packages along with sources of support, including newsgroups/mailing lists, web pages provided by the vendors, and the vendor's technical support email address. Other lists news:sci.stat.consult - General issues in statistics. The content of this web site should not be construed as an endorsement of any particular web site, book, or software product by the University of California.
Classics in Psychology An internet resource developed byChristopher D. Green , ISSN 1492-3173 (Return to Classics index) Last updated . 19th- & 20th-Century Psychology Can't find what you want? Ancient Thought Plato. Aristotle. Aristotle. For additional works by the Presocratics, Plato, Aristotle, Hippocrates, Euclid, Lucretius, Epictetus, Galen, Plotinus, and Augustine, see the Links to Documents at Other Sites page. Medieval & Renaissance Thought For works by Aquinas, Roger Bacon, Pico, and Machiavelli see the Links to Documents at Other Sites page. Modern Philosophical Thought Berkeley, George. (1732). Bowen, Francis. (1860). McCosh, James. (1874). Herbart, J. Fiske, John. (1902). Royce, Josiah. (1902). Stumpf, Carl. (1930). Titchener, E. Creighton, J. For additional works by Descartes, Hobbes, Pascal, Locke, Leibniz, Spinoza, , Voltaire, Hume, Smith, Malthus, Kant, Hegel, Marx, Mill, Brentano, Mach, Peirce, James, Dewey, Husserl, Russell, Mead, and Merleau-Ponty see the Links to Documents at Other Sites page.
Mining of Massive Datasets The book has now been published by Cambridge University Press. The publisher is offering a 20% discount to anyone who buys the hardcopy Here. By agreement with the publisher, you can still download it free from this page. --- Jure Leskovec, Anand Rajaraman (@anand_raj), and Jeff Ullman Download Version 2.1 The following is the second edition of the book, which we expect to be published soon. There is a revised Chapter 2 that treats map-reduce programming in a manner closer to how it is used in practice, rather than how it was described in the original paper. Version 2.1 adds Section 10.5 on finding overlapping communities in social graphs. Download the Latest Book (511 pages, approximately 3MB) Download chapters of the book: Download Version 1.0 The following materials are equivalent to the published book, with errata corrected to July 4, 2012. Download the Book as Published (340 pages, approximately 2MB) Gradiance Support Other Stuff Jure's Materials from the most recent CS246.