Resource Library

This activity uses Microsoft Excel to estimate the population variance of grouped data two ways: the variance within a group and the variance between groups. This activity accompanies Section 7.3 of Data Matters.

This article describes a dataset of days in office of US Presidents with outliers that are not mistakes or unusually high or low observations. The data illustrate that outliers need not be errors but could be particularly interesting cases and that data displays may differ in their ability to reveal interesting data structure. Key Words: Inliers; Interpretation in context.

The dataset presented in this article referes to game-by-game information for Mark McGwire and Sammy Sosa during summer of 1998. This data can be used to demonstrate graphical displays, categorical data analysis, analysis of variance, logistic regression, and smoothing methods for Poisson and binomial data.

This section of an online textbook discusses calculating the exact probability using observed sets of frequencies, constructing frequency tables, and computing p-values. Exercises and answers are provided.

This worksheet activity teaches random sampling and theoretical probabilities by simulating the effects of randomly assigning newborn babies to their mothers. Students will perform trials and keep track of results, then use the information to deduce properties of random sampling. The relation website is an applet that simulates the process automatically.

This is a collection of activities as Java applets that can be used to explore probability and statistics. Each activity is supplemented with background information, activity instructions, and a curriculum for the activity.

Users can select from detailed tables and geographical comparison tables to generate data from the 2000 Census.

This exercise uses descriptive statistics to analyze a data set about how rats respond to rock music vs. classical music.

This set of exercises asks students to model relationships and test them based on the chi-square distribution. The data used is based on testosterone levels and delinquency rate of American military men.

This activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), that not all histograms are easy to classify, that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.). Key words: Histogram, shape, normal, uniform, skewed, symmetric, bimodal