Resource Library

This site gives an explanation, a definition and an example of ANOVA for regression. Topics include analysis of variance calculations for simple and multiple regression, and F-statistics.

This site gives an explanation, a definition and an example of multiple linear regression. Topics include confidence intervals, tests of significance, and squared multiple correlation.

This site gives an explanation, a definition and an example of inference in linear regression. Topics include confidence intervals for intercept and slope, significance tests, mean response, and prediction intervals.

This online introductory statistics textbook covers basic descriptive, statistical, and graphical procedures for analyzing data sets and contains three data sets and a practice final exam. Chapter headings include: Descriptive Statistics, Probability, Resampling, Discrete Probability Models, Continuous Probability Models, Central Limit Theorem, Confidence Intervals, Tests of Hypotheses, Estimation of Effect: Two Independent Samples, Design of Experiments, and Regression. The relation to this site includes exercises.

The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.

This source defines and explains variance and standard deviation.

This applet allows you to manipulate the starting population, age-class survival rates, and age-class fecundity rates over 10 generations for up to 6 age classes. The default gives you the same population size for each age class as well as the same fecundity rate and survival rates. Move the sliders for each age class to manipulate each of these factors. You will see the relative proportions of each age class will change over time, but will eventually reach a stable age distribution.

This site provides case studies which cover subject areas including: analysis of variance, boxplots, confidence intervals, contrast among means, correlated t-test, correlation, histograms, independent groups t-test, regression, repeated measures ANOVA, and t-tests.

Gives a very brief explanation of Spearman' rho and how it differs from Pearson's r.

This lesson on the Poisson distribution explains the theory, history, and applications of the distribution and gives examples and a multiple choice test.