# Categorical ANOVA

• ### Penn State STAT 502: Analysis of Variance and Design of Experiments

This is a graduate level course/collection of lessons in analysis of variance (ANOVA), including randomization and blocking, single and multiple factor designs, crossed and nested factors, quantitative and qualitative factors, random and fixed effects, split plot and repeated measures designs, crossover designs and analysis of covariance (ANCOVA). Perfect for students and teachers alike looking to learn/acquire materials on ANOVA.

• ### HyperStat Online: Ch. 12 Introduction to Between-Subjects ANOVA

Analysis of variance (ANOVA) is used to test hypotheses about differences between two or more means. The t-test based on the standard error of the difference between two means can only be used to test differences between two means. When there are more than two means, it is possible to compare each mean with each other mean using t-tests. However, conducting multiple t-tests can lead to severe inflation of the Type I error rate. (Click here to see why) Analysis of variance can be used to test differences among several means for significance without increasing the Type I error rate. This chapter covers designs with between-subject variables.

• ### HyperStat Online: Ch. 13 Factorial Between-Subjects ANOVA

When an experimenter is interested in the effects of two or more independent variables, it is usually more efficient to manipulate these variables in one experiment than to run a separate experiment for each variable. Moreover, only in experiments with more than one independent variable is it possible to test for interactions among variables.  Experimental designs in which every level of every variable is paired with every level of every other variable are called factorial designs.

• ### HyperStat Online: Ch. 14 Within-Subjects/Repeated Measures ANOVA

Within-subject designs are designs in which one or more of the independent variables are within-subject variables. Within-subjects designs are often called repeated-measures designs since within-subjects variables always involve taking repeated measurements from each subject. Within-subject designs are extremely common in psychological and biomedical research.

• ### Two-Way Analysis of Variance

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.
• ### One-Way Analysis of Variance (ANOVA)

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.
• ### Friedman Two Way Analysis of Variance by Ranks

This tutorial explains the theory and use of the Friedman Two Way ANOVA and demonstrates it with an example on exam scores, homework scores, and project scores. Data is given as well as SPSS and Minitab code.
• ### Which Statistic When?

This tutorial introduces various statistics used to analyze and summarize data. The tutorial covers both the arithmetic and geometric means, median, mode, standard deviation, coefficient of variation, skewness, kurtosis, quadrants, and histrogram analysis. The application is flow cytometry, but others may use this tutorial as well.
• ### Analysis Tool: One- and Two-Way Analysis of Variance (ANOVA) JAVA Applet

This applet allows users to input their own data and perform one- and two-way Analyses of Variance. Key Word: ANOVA.

• ### Data Collection: STAT LABS: Data

These datasets come from the book "STAT LABS: Mathematical Statistics Through Applications." Below the link for each dataset are descriptions of the variables for that dataset. Datasets are in text format and address topics such as maternal smoking and infant health, video games, radon, cytomegalovirus DNA, HIV, crab molting, voting, snow gauge calibration, down syndrome, and tape drive quality.