This survey assesses statistical literacy. The survey focuses on the general use of informal statistics in everyday situations: reading and interpreting tables and graphs involving rates and percentages.
This article discusses teaching causality without being discipline specific. It explains the causal differences between description, prediction and explanation.
This paper presents rules for determining whether an index variable in such a table is part or whole depending on whether the associated margin value is an average, a sum or a 100% sum. Tables with missing margin values -- date-indexed tables, half tables and control tables -- are analyzed. Recommendations are made to improve reader understanding of any table involving rates or percentages.
This paper presents three graphs that are used in teaching students majoring in business and the humanities. These graphs show the influence of confounding, the meaning of statistical significance, and the influence of confounding on statistical significance.
This website provides links to instructions for performing basic statistics such as confidence intervals, hypothesis tests, discrete distributions, linear regression, etc. for TI 83, TI 84, and TI 86 calculators.
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 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 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 article describes a dataset containing information on economic class of passengers and mortality rates from the sinking of the Titanic. The dataset can be used to foster statistical thinking by giving students the data and asking them to determine the source.
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.
