This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: iterative solutions to non-linear equations, score equations for exponential class variables, Newton-Raphson vs. Fisher’s Scoring, Logistic Regression for an R × 2 tables, saturated model, odds ratios when rows are not ordinal, goodness of fit, likelihood ratio statistic for nested models, and residuals.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: generalized IxJ contingency tables, degrees of freedom, Fisher's exact test, and generalized odds ratio.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: absolute/relative measures, number needed to treat (NNT), relative risk, odds ratio, the delta method (with a multivariate extension), and a variance covariance matrix.
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: Wald test, score test, likelihood-ratio test, large sample confidence intervals, and the F distribution.
Epidemiology is the study of the distribution and determinants of human disease and health outcomes, and the application of methods to improve human health. This course examines the methods used in epidemiologic research, including the design of epidemiologic studies and the collection and analysis of epidemiological data. Perfect for students and teachers wanting to learn/acquire materials for this topic.
Random is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library.
This resource defines and explains Chi square. It takes the user through 5 different categories: 1) Testing differences between p and pi 2) More than two categories 3) Chi-square test of independence 4) Reporting results 5) Exercises.
This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet in which users can manipulate the parameters to see how the distribution changes. The parameters are described on the main page as well as situations that would use each distribution. The equations of the distributions are not given. To select between the different applets you can click on Statistical Theory, Probability Distributions and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/
This page calculates probabilities for a Poisson distribution.