Resource Library

This tutorial exposes students to conducting multiple comparisons in SPSS. This html based tutorial provides extensive screen shots and an example data set. Topics covered in the tutorial include one way ANOVA, preplanned contrasts, Bonferroni, Post Hoc Tukey's HSD, and Scheffe's multiple contrasts.

This tutorial exposes students to conducting chi-square tests in SPSS. This html based tutorial provides extensive screen shots and an example data set.

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 presents data for examining the ability of individuals to choose numbers randomly. Three datasets of six-tuples selected by a lottery game, generated by S-Plus, and chosen by college students can be compared using descriptive statistics and goodness of fit tests to explore bias and randomness. Key Words: Boxplots; Chi-squared tests; Minimum gap; QQ plots.

The datasets described in this article contain information for all National Football League (NFL)regular season and playoff games played from 1993 to 1996. In addition to game scores, the data give oddsmakers' pointspreads and over/under values for each game. Key Words: Predictions; Wagering.

This article describes a dataset containing energy use data for single-family homes and monthly weather data in the Boston area over a seven year period. The data can help illustrate concepts like central tendency, dispersion, time series analysis, correlation, simple and multiple regression, and variable transformations. Key Words: measurement; forecasting.

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 provides a data collection and analysis activity for illustrating simple linear regression and outlier analysis. The activity was designed to involve students in the process of data collection and to motivate studying the relationship between two quantitative variables. Students collect data on occurrences of letters in English text. These data are used to study the relationships between how often a letter occurs in English text, and: (1) the letter's Morse Code units and (2) the relative frequency of Scrabbleä‹¢ game tiles for the letter. Worksheets and answers to the activities are provided.

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.

The dataset presented in this article comes from a South African study of growth of children. This data is a useful example of Simpson's paradox. Key Words: Categorical data; Comparing proportions.