Resource Library

This glossary defines and explains statistical terms for introductory students. The glossary can be shown in alphabetical order or in suggested learning order. Click on the topic of interest to see the definition. Use the arrows at the bottom to proceed to the next topic or click the blue dot to return to the contents page.

This glossary gives definitions for numerous statistical terms, concepts, methods, and rules.

These pages from the University of Melbourne explain statistical concepts using various examples from medicine, science, sports, and finance. The intent is not computational skill but conceptual understanding. Some pages also contain data.

CAST contains three complete introductory statistics courses, one advanced statistical methods course, and additional modules. Each introductory course presents the same topics, but with different applications. The first is a general version, the second is a biometric version with examples relating to biological, agricultural and health sciences, and the third is a business version. Each course comes in a student version and a lecture version. The additional modules cover Multiple and Nonlinear Regression, Quality Control, and Simulation. Registration is required, but free. Individuals or classes can register.

This page gives a history of notation and symbols and who developed them for combinatorial analysis, the normal distribution, probability, and statistics. Quotes from the first papers to use these symbols are also given.

This tutorial opens with a survey on polling. Upon completing the survey, students are taken through an election example which uses polling to explain random sampling, bias, margin of error, and confidence intervals.

This page from the Bureau of Labor Statistics provides data and statistics on Inflation & Consumer Spending, Wages, Earnings, & Benefits, Productivity, Safety & Health, International Labor, Occupations, and Demographics. Data is in Excel, html, or pdf format.

This tutorial introduces the statistical software SPSS for Windows users. Topics covered include: The Basics, Data, Descriptive Statistics, Chi-square & T-tests, Correlations & Regression, Oneway ANOVA, Factorial ANOVA.

This collection of datasets from Harvard University covers many ecological topics from insects to hurricanes. Each dataset's description includes the name of the investigator, dates of collection, location, abstract, and method of collection. The metadata file for each dataset provides descriptions of the variables. Please read the terms of agreement before use.

This page helps readers know which statistcal tests are appropriate for the different types of data. Two charts display the information. A discussion of study design and sample size, as well as exercise questions with solutions are also provided.