Resource Library

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 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 a dataset containing the 1970 draft lottery information, which illustrates a nonrandom procedure. Key Words: Chi-square; Correlation; Exploratory data analysis; Graphical analysis; Randomness; Regression.

This article presents a dataset containing actual monthly data on computer usage in Best Buy stores from August 1996 to July 2000. This dataset can be used to illustrate time-series forecasting, causal forecasting, simple linear regression, unequal error variances, and variable transformation. Key Words: Model-building; Seasonal Variation.

This section of an online textbook discusses the correlation coefficient and illustrated it visually through graphs. It explains calculations as well as how scatter plots can describe data. It covers significance tests for relationships, the Spearman rank correlation and the regression equation. Exercises and answers are included.

This site provides numerous datasets for graphical display topics including linear, exponential, logistic, power rule, periodic, and other bivariate scatterplots, histograms, and other univariate data. Each data set is accompanied with a description, file format options, and a sample graph.

This is a virtual spinner applet, which allows you to change spinner regions and the number of spins. It records the results and displays the data in a histogram.

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.

Using a parameter it's possible to represent a property of an entire population with a single number instead of millions of individual data points. There are a number of possible parameters to choose from such as the median, mode, or interquartile range. Each is calculated in a different manner and illuminates the data from a different point of view. The mean is one of the most useful and widely used and helps us understand populations. A population is simulated by generating 10,000 floating point random numbers between 0 and 10. Sample means are displayed in histograms and analyzed.

This page shows how elements of a systems can be eliminated as causes in problem troubleshooting. The principles of twenty questions are frequently used in the business world to conduct computerized searches of massive data bases. These are called a binary searches and are one of the fastest search methods available. To conduct binary searches, data must be sorted in order or alphabetized. The computer determines which half of the list contains the item. The half containing the item is divided in half again and the process repeated until the item is found or the list can no longer be divided. Problem solvers should avoid focusing on the cause and instead ask which elements of the system can be eliminated as causes.