Resource Library

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 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."

In this free online video program, students will learn that "causation is only one of many possible explanations for an observed association. This program defines the concepts of common response and confounding, explains the use of two-way tables of percents to calculate marginal distribution, uses a segmented bar to show how to visually compare sets of conditional distributions, and presents a case of Simpson's Paradox. The relationship between smoking and lung cancer provides a clear example."

In this free online video program, students will learn that "statistics can be used to evaluate anecdotal evidence. This program distinguishes between observational studies and experiments and reviews basic principles of design including comparison, randomization, and replication. Case material from the Physician's Health Study on heart disease demonstrates the advantages of a double-blind experiment."

This chapter of the NIST Engineering Statistics handbook presents information on the statistical modeling of an engineering process. It contains an introduction, discussion of the assumptions, information about data collection and analysis, a discussion of what can be concluded from different process models, and case studies.

This chapter of the NIST Engineering Statistics handbook provides information on the proper design of experiments. It contains an introduction, a discussion of assumptions, a description of different design types, a discussion of the analysis of data, and case studies.

This part of the NIST Engineering Statistics handbook contains case studies for the process improvement chapter, which deals with design of experiments.

This part of the NIST Engineering Statistics handbook contains case studies for the process or product monitoring and control chapter.

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 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.