The dataset presented in this article contains body measurements for 252 men and can be used to illustrate multiple regression and to provide practice in model building.
This article presents a dataset based on an industrial case study using design of experiments. It can be used to discuss sample size, power, statistical significance, interaction terms, Type I and Type II errors, the role and importance of the error term, design of experiments, and analysis of variance.
This article describes a dataset containing monthly household electric billing charges for ten years. The data can be used to illustrate graphing, descriptive statistics, correlation, seasonal decomposition, a variety of smoothing methods, ARIMA models, forecasting, and multiple regression.
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.
The dataset presented in this article contains information on the prices and weights of diamond stones; it can be used to illustrate simple linear regression and encourage students to think critically about the appropriateness of a model. The data is in .dat format. Key Words: Extrapolation; Interpretation of intercept; Model-building; Transformations.
This article describes a dataset containing information for 25 brands of domestic cigarettes. The dataset can be used to illustrate multiple regression, outliers, and collinearity.
This article presents a dataset containing physical measurements for 507 physically active individuals. These data can be used to demonstrate simple descriptive statistics, least squares and multiple regression, or discriminant and classification analysis. The data are in .dat format.
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.
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 provides the salary and performance data for non-pitchers for the 1992 Major League Baseball season. Exploratory data analysis is used to determine a suitable regression model for the data. Key Words: Model selection and validation; Stepwise model selection.
