This case study explores statistics on divorce rates using Markov chains. Two closely related statistics are presented: the chance of divorcing in a given year and the chance of divorcing over the lifetime of a marriage. Accompanying teacher instructions are found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov_notes.html
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.
The online "Engineering Statistics Handbook" provides a section (4.6 Case Studies in Process Modeling) using detailed realistic examples from physical science and engineering applications. Examples in Load Cell Calibration, Alaska Pipeline Ultrasonic Calibration, Ultrasonic Reference Block Study, and Thermal Expansion of Copper Case Study are presented in a step-by-step manner.
The eighth chapter of an online Introduction to Biostatistics course. Lecture notes are provided. Additionally, links for additional reading and exercises with solutions are provided.
This tutorial on the One Sample t test includes its definition, assumptions, hypotheses, and results. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
This tutorial on Simple Linear Regression includes its definition, assumptions, and characteristics as well as related statistics and hypothesis test procedures. One section instructs users to perform simple linear regression in the WINKS software, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
This applet allows the user to adjust a (1st shape) and b (2nd shape) parmaters of the Beta distribution with a slider or manual input. The applet allows the user to fix the x and or y axes. The user immediately sees how this affects the the shape of the graph as well as the variance and the expected value. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/BetaDensityApplet.html
By changing the number of degrees of freedom in a t-distribution, students can see how the pdf changes. They also have the option of overlayng the standard normal curve so that they can see the convergence.
