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: linear association, correlation coefficient, ridits/modified ridits, nonparametric methods, Cochran-Armitage Trend test,
This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: multinomial distribution, LaGrange multipliers, Exact Multinomial Test (EMT), the Pearson statistic, and goodness of fit.
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.
This is a graduate level introduction to statistics including topics such as probabilty/sampling distributions, confidence intervals, hypothesis testing, ANOVA, and regression. Perfect for students and teachers wanting to learn/acquire materials for this topic.
This is a graduate level survey course that stresses the concepts of statistical design and analysis in biomedical research, with special emphasis on clinical trials. Perfect for students and teachers wanting to learn/acquire materials for this topic.
This chapter explains the structure/steps of hypothesis testing, the concept of significance, the relationship between confidence intervals and hypothesis testing, and Type I/II errors.
This text explains the differences between t-tests, z-tests, tests with proportions, and tests of correlation.
Measures of the size of an effect based on the degree of overlap between groups usually involve calculating the proportion of the variance that can be explained by differences between groups. This resource outlines different approaches to measuring this proportion.
This applet allows the user to simulate a race where the results are based on the roll of a die. For each outcome of the die, the user chooses which player moves forward. Then that car moves forward the given number of spaces. Users can experiment with the race by determining which player will win more often based on the rules that they specify.