Resource Library

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 Multiple Regression and demonstrates it with an example on SAT scores and GPA. Data is given as well as SPSS and Minitab code.

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 One-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 Pearson's Product Moment Coefficient of Correlation and demonstrates it with an example on GPA and test scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of the Wilcoxon Matched-Pairs Ranks test and demonstrates it with an example on project quality. 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 the Sign Test and demonstrates it with an example on intervention methods. Data is given as well as SPSS and Minitab code.

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.

Song playfully celebrates Bayesian inference and includes various vocabulary such as coherence, prior, and exchangeable. May be sung to the tune of "Strangers in the Night" (Kaenpfert/Singleton/Snyder). Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.