Resource Library

This Flash applet provides an introduction to simple linear regression for introductory statistics students. It combines a brief narrated animation with an interactive scatterplot function. Students are able to place points on the scatterplot by clicking with a mouse or typing X-Y coordinates. Students use these points to learn about the best fit line by placing a guess on the plot and comparing it with the least squares line. Students also learn about the value of the correlation coefficent and points that would be considered outliers. Students may also specify a value of x (within the range of the data) and obtain the resulting predicted value.

This lesson plan uses the Birthday Paradox to introduce basic concepts of probability. Students run a Monte Carlo simulation using the TI-83 graphing calculator to generate random dates, and then search for matching pairs. Students also perform a graphical analysis of the birthday-problem function. Key Words: Permutations; Explicit Function; Recursive Function; Modeling.

This page explores Benford's Law: For naturally occurring data, the digits 1 through 9 do not have equal probability of being the first significant digit in a number; the digit 1 has greater odds of being the first significant digit than the others. This law can be used to catch tax fraud because truly random numbers used by embezzlers do not meet this condition.

This is an example of "growing" a decision tree to analyze two possible outcomes. The tree's branches examine the two possible conditions of employee drug use with corresponding probabilities. This example looks at the final outcome probabilities of being correctly and incorrectly identified versus testing accuracy.

This video is an example of what is known in psychology as selective attention. When a person is instructed to only focus on the number of times a ball is passed between players wearing a white shirt it is sometimes difficult to see what else is going on.

This webpage uses the criminal trials in the US Justice system to illustrate hypothesis testing, type I error, and type II error. An applet allows the user to examine the probability of type I errors and type II errors under various conditions. An applet allows users to visualize p-values and the power of a test. Keywords: type I error, type II error, type one error, type two error, type 1 error, type 2 error

This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course. These objectives were developed for a one semester general education introductory statistics course. The objectives cover the broad categories of Graphics, Summary Statistics, The Normal Distribution, Correlation and Scatterplots, Introduction to Regression, Two way Tables, Data Collection and Surveys, Basic Probability, Sampling Distributions, Confidence Intervals, Tests of Hypothesis, and T-distributions.

This excerpt from Engineering Statistics Handbook gives a definition for and examples of outliers. A sub-page also discusses Grubbs' Test for Outliers

This lesson describes bootstrapping in the context of a statistics class for psychology students.

This exercise includes a discussion on comparing data with very different sample sizes and nonhomogeneity of variance. The data comes from a study on the behavior of pregnant women with regard to cigarette smoking.