Probability

This website is a resource of teaching methods and approaches that instructors at all levels of statistics education can use to generate student interest in pursuing more study or a career in the field of statistics.

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 Chi-Square Test for goodness of fit and demonstrates it with an example on mastery test 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.