Resource Library

This page, part of the NIST Engineering Statistics handbook, contains links to web pages which have tables of values for various distributions.

This part of the NIST Engineering Statistics handbook contains case studies for the production process characterization chapter.

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 chapter of the NIST Engineering Statistics handbook "presents techniques for monitoring and controlling processes and signaling when corrective actions are necessary." It contains an introduction to process control, a discussion of acceptance sampling, introductions to control charts and time series modeling, tutorials for background information, and case studies.

This page lists the laboratories and java projects for a course in advanced statistics.

This part of the NIST Engineering Statistics Handbook contains case studies for Exploratory Data Analysis. Some of the topics include normal and uniform random numbers, reliability using airplane glass failure times, and analysis of primary factors using ceramic strength.

This Electronic Statistics Textbook offers training in the understanding and application of statistics ... and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. Quoted from the index page of the text.

This lesson deals with the statistics of political polls and ideas like sampling, bias, graphing, and measures of location. As quoted on the site, "Upon completing this lesson, students will be able to identify and differentiate between types of political samples, as well as select and use statistical and visual representations to describe a list of data. Furthermore, students will be able to identify sources of bias in samples and find ways of reducing and eliminating sampling bias." A link to a related worksheet is included.