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 dataset contains the time of birth, sex, and birth weight for 44 babies born in one 24-hour period at a hospital in Brisbane, Australia. The data can be used for studying some common distributions like the normal, binomial, geometric, Poisson, and exponential.
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 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.
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.
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 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 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 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.
