# Simulation

• ### Categorical Data

This site gives a definition and an example of categorical data. Topics include two-way tables, bar graphs, and segmented bar graphs.
• ### Linear Regression

This site gives an explanation, a definition and an example of linear regression. Topics include least-squares, residuals, extrapolation, outliers, and influential observations.

• ### Correlation

This site gives an explanation, a definition and an example of correlation. Topics include correlation coefficient and rŒ_.

• ### Inference in Linear Regression

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.
• ### Monte Carlo Estimation for Pi

This is the description and instructions for the Monte Carlo Estimation of Pi applet. It is a simulation of throwing darts at a figure of a circle inscribed in a square. It shows the relationship between the geometry of the figure and the statistical outcome of throwing the darts.
• ### Rice Virtual Lab in Statistics

This site has a wide collection of statistical resources inluding an online textbook covering first-year non-calculus based statistics (e.g. Normal distribution, ANOVA, Chi-Square), a simulation/demonstration section containing Java Applets on these first-year topics (ANOVA, Binomial Distribution,Central Limit Theorem, Chi Square, Confidence Interval, Correlation, Central Tendency, Effect Size, Goodness of Fit, Histogram, Normal Distribution, Power, Regression, Repeated Measures, Restriction of Range, Sampling Distribution, Skew, t-test, Transformations), and case studies covering the topics in the first-year statistics course. There is also a page with some basic statistical analysis tools that will aid in doing the computations if you have a Java enabled browser.  The source code for these resources can also be downloaded from this site.

• ### Probability Models JAVA Applet Sourcecode

This applet simulates rolling dice and displays the outcomes in a histogram. Students can choose to roll 1, 2, 6, or 9 dice either 1, 10, 20, or 100 times. The outcome studied is the sum of the dice and a red line is drawn on the histogram to show expected number of occurences of each outcome.