This free online video program uses historical anecdotes and contemporary applications to introduce the series which "explores the vital links between statistics and our everyday world. The program also covers the evolution of the discipline."
This laboratory introduces students to the basics of the Minitab software. Students make use of a basic example (water consumption and temperature) to introduce students to manipulation of data, calculation of descriptive statistics, creation of histograms, boxplots and scatterplots. Students are asked to hand in the results they have produced. Accompanying documents give model solutions.
This online textbook provides information on the statistical analysis of nutritional data. Techniques covered include data cleaning, descriptive statistics, histograms, graphics, scatterplots, outlier identification, regression and correlation, confounding, and interactions. Each chapter includes exercises with real data and self-tests to be used with SPSS.
This activity guides students through the process of checking the validity of data, performing summary analysis, constructing box plots, and determining whether significant differences exist. The data comes from a study of mineral levels in older adults and is available in Minitab, Excel, SAS, and text formats.
This site contains data sets to help teach a Chance course and help students understand issues that may not be found in a standard statistics text. Topics covered include: mean, median, random walks, regression, correlation, and more.
This reference resource explores the use of clickers, or personal response systems, in the classroom. Main points of discussion include what clickers are, who is using them, what makes them unique, why they are considered significicant, the downsides, and teaching and learning implications.
This chapter of the NIST Engineering Statistics handbook "describes the terms, models and techniques used to evaluate and predict product reliability." It contains an introduction, discussions on the assumptions, and sections on reliability data collection and analysis.
This chapter of the NIST Engineering Statistics handbook "presents the background and specific analysis techniques needed to compare the performance of one or more processes against known standards or one another." It contains an introduction and information about comparisons with one process, two processes, and three or more processes or samples. Topics include outliers, trends, confidence intervals for means and proportions for one sample. Also included are materials on ANOVA, Kruskal Wallis tests, tests for equivalence of variances, variance components, chi-square tests for contingency tables and multiple comparisons.
This part of the NIST Engineering Statistics handbook contains case studies for the process improvement chapter, which deals with design of experiments.
