Resource Library

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 online resource is intended to help students understand concepts from probability and statistics and covers many topics from introductory to advanced. You can follow the progression of the text, or you can click on a topic on the left. Key Words: Alpha Reliability; Analysis of Covariance (ANCOVA); Analysis of Variance (ANOVA); Bayesian Analysis; Bias; Binomial regression; Bonferroni adjustment; Bootstrapping; Categorical modeling; Central limit theorem; Chi-squared test; Clinical significance; Cluster analysis; Coefficient of variation; Confidence Intervals; Contingency Table; Controlled trial; Confounders; Correlation; Dimension reduction; Discriminant function analysis; Frequency; Normal; Poisson; Probability Distribution; Effect; Error; Factor Analysis; Goodness of Fit; Heteroscedasticity; Hypothesis Testing; Independence, Interactions; Kappa Coefficient; Latin Squares; Least Squares Means; Likert scales; Linear Regression; Logistic Regression; Multivariate ANOVA (MANOVA); Mixed Modeling; Multiple Linear Regression; Nonparametric models; Odds ratio; P Values; Path Analysis; Percentiles; Polynomial Regression; Power; PRESS; Probability; Relative Frequency; Repeated Measures; Sample Size; Sampling; Sensitivity; Stepwise regression; Structural equation modeling; T Test; Transformation; Validity.

This tutorial explains the theory and use of the Sign Test and demonstrates it with an example on intervention methods. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of two-way ANOVA and demonstrates it with an example on final exam scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of Student's t-test and demonstrates it with an example on final exam scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of Student's t-test for matched pairs and demonstrates it with an example on project quality. Data is given as well as SPSS and Minitab code.

This tutorial describes various measures of central tendency, their theory and use, and demonstrates them with an example on final exam scores. Data is given as well as SPSS and Minitab code. Key Words: Mean; Median; Mode; Variance; Standard Deviation.

This tutorial explains the theory and use of the Mann-Whitney test and demonstrates it with an example on traditional lecture versus computer-based teaching. Data is given as well as SPSS and Minitab code.