This site is an index of modules which cover probability and statistics topics including basic probability, random variables, moments, distributions, data analysis including regression, moving averages, exponential smoothing, and clustering.
DataCounts! is an interactive website designed to help integrate social statistics into the classroom setting. Each collection contains a wide variety of datasets that can be viewed online with WebCHIP. DataCounts! also houses a collection of teaching modules that have been created by teachers across the country to integrate social science data into their classes.
StatVillage is a hypothetical village in Canada. Homes in StatVillage are laid out in a system of blocks on a rectangular grid with 8 homes per block. In the middle of each group of 8 homes is a playing area. Houses are addressed using a block and unit-within-block system. Services (e.g. food stores, shops) are located on the periphery of the village and are not shown on the map. Households can be selected for a survey by using a clickable map.
This site lists a set of case studies that cover regression topics, random number calculations of pi, as well as limit theorems. On the individual case study pages are the descriptions and/or instructions.
This page is a guide to writing and using statistics in the field of science. It is aimed at biology students. It contains information on formatting and the use of tables as well as links to pages about frequency analysis, t-tests, and regression.
This chapter of the NIST Engineering Statistics handbook describes Exploratory Data Analysis with an introduction, a discussion of the assumptions, a description of the techniques used, and a set of case studies.
This online, interactive lesson on random samples provides examples, exercises, and applets concerning sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample covariance and correlation.
This online, interactive lesson on point estimation provides examples, exercises, and applets concerning estimators, method of moments, maximum likelihood, Bayes estimators, best unbiased estimators, and sufficient, complete and ancillary statistics.
