The International Society for Bayesian Analysis (ISBA) was founded in 1992 to promote the development and application of Bayesian analysis. By sponsoring and organizing meetings, publishing the electronic journal Bayesian Analysis, and other activities, ISBA provides an international community for those interested in Bayesian analysis and its applications.
This site offers separate webpages about statistical topics relevant to those studying psychology such as research design, representing data with graphs, hypothesis testing, and many more elementary statistics concepts. Homework problems are provided for each section.
The goal of WISE is to provide students and teachers of statistics easy access to a wide range of resources that are freely available on the internet. We invite you to explore our website and enjoy many wonderful statistical materials from around the world.
This text was written for an introductory class in Statistics suitable for students in Business, Communications, Economics, Psychology, Social Science, or liberal arts; that is, this is the first and last class in Statistics for most students who take it. It also covers logic and reasoning at a level suitable for a general education course. SticiGui provides text, interactive tools, lecture videos, sample exam reviews, and more for a course in basic statistical concepts.
The Cornell Statistical Consulting Unit distributes a periodic electronic newsletter, StatNews. This newsletter discusses applications of statistics that are commonly encountered in research and teaching.
Newsletter issue of 'StatNews' distributed by the Cornell Statistical Consulting Unit on survival analysis.
This page supports an in-class exercise that highlights several key Bayesian concepts. The scenario is as follows: a large paper bag contains pieces of candy with wrappings of different color, and we are interested in learning about the unknown proportion of yellow-wrapped pieces of candy. After completing the exercises, we will be familiar with the following concepts and ideas: probability distributions can quantify degree of belief, prior distribution, posterior distribution, sequential updating, conjugacy, Cromwell’s Rule (http://en.wikipedia.org/wiki/Cromwell's_rule), the data overwhelm the prior, Bayes factors, Savage-Dickey density ratio, sensitivity analysis, coherence.
Find the best linear fit for a given set of data points and residuals (or let this app show you how it is done).
Adjust regression parameters to bend and shift a two-dimensional polynomial surface.
Check how your Bayes factor conclusion depends on the r-scale parameter.