This article describes Galileo's data on falling bodies and projectiles and its use as an aid in teaching polynomial and nonlinear regression. Key Words: Independent and dependent variables; Graphical analysis.
This article presents data from 1997 Big Ten Conference men's basketball games involving the University of Iowa Hawkeyes. The data can be used to demonstrate bivariate statistical inference techniques such as confidence regions, paired comparisons, and simultaneous confidence intervals. Key Word: Bivariate data; Scatterplot.
This dataset contains a number of variables like birth rate, death rate, life expectancy, and Gross National Product for 97 countries. Suggested activities are geared toward non-mathematicians and include exploratory graphical analyses to answer several central questions. Key words: boxplot, scatterplot, population growth
This article addresses a dataset on public school expenditures and SAT performance. Key Words: Multiple regression; Omitted variable bias; Partial correlation; Scatterplot.
This article describes a dataset on life expectancies, densities of people per television set, and densities of people per physician in various countries of the world. The example addresses correlation versus causation and data transformations. Key Word: Prediction.
This article describes a dataset containing information on bacterium culturing. Students can use graphical methods, one-way and two-way ANOVA, and multiple polynomial regression to estimate the optimal conditions for bacteria growth. Key Words: Analysis of variance; Exploratory data analysis; Interactions; Optimisation; Outlier.
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 site provides applets, lessons, and objectives for learning about conditional probability. The applet activity introduces multiple-outcomes events and computing probabilities.
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 applet simulates randomly assigning newborn babies to families and measures the number of matches, or instances when a baby is assigned to its real family. The applet keeps track of each trial and records the information in a histogram. The idea is to teach theoretical values associated with random sampling. The relation website is a worksheet activity to accompany the applet.
