G*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, ztests and some exact tests. G*Power can also be used to compute effect sizes and to display graphically the results of power analyses.
G*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, ztests and some exact tests. G*Power can also be used to compute effect sizes and to display graphically the results of power analyses.
This resource defines a pie chart. It also allows the user to input values to create their own graphs. The user has control over the title, up to 15 slices, the color of each slice, and can choose a 3-D option.
This online, interactive lesson on probability spaces provides examples, exercises, and applets that cover conditional probability, independence, and several modes of convergence that are appropriate for random variables. This section also covers probability space, the paradigm of a random experiment and its mathematical model as well as sample spaces, events, random variables, and probability measures.
This online, interactive lesson on geometric models provides examples, exercises, and applets which include Buffon's Problems, Bertrand's Paradox, and Random Triangles.
This applets on this site include: interactive graphs of many distribution models; a collection of computer generated games; a collection of data modeling aids including curve fitting, wavelets, matrix manipulations, etc.; p-values, quantiles & tail-probabilities calculations; virtual online probability experiments and demonstrations; and a large collection of statistical techniques for online data analysis, visualization, and integration.
This online, interactive lesson on the renewal processes provides examples, exercises, and applets which include renewal equations and renewal limit theorems.
This online, interactive lesson on finite sampling models provides examples, exercises, and applets that include hypergeometric distribution, multivariate hypergeometric distribution, order statistics, the matching problem, the birthday problem, and the coupon collector problem.
SalStat is an small application for the statistical analysis of scientific data (with a special concentration on psychology). It can already do 18 kinds of descriptive statistics, t tests (paired, unpaired and one sample), 3 kinds of correlations linear regression and point biserial tests, and single factor ANOVA (both within and between subjects). Data are entered on an easy-to-use datagrid like a spreadsheet, and all the analyses are driven by menus and dialog boxes. Output can be formatted to HTML.
This online software allows you to load data and make professional-looking graphs with it. Graph types are basic (scatterplot, line plot, bar charts, etc.), statistical (histograms, box plots), scientific (error bars, heat map, contour), 3D charts, and financial (e.g. time series). Other graphs are available with the paid pro version. Log in is required, which allows you to upload data and save it for next use.
This is a chapter on ethics excerpted from a book on data science. The book is “Modern Data Science with R,” and the authors are Benjamin J. Baumer, Daniel T. Kaplan, and Nicholas J. Horton. The chapter presents several ethical dilemmas, then a framework to use when evaluating ethical issues. Then it discusses the dilemmas again, now resolving them.