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In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphicalfigures to complement outcomes from parametric Two-Way ANOVA.
List of contents
1. Introduction.2. Data Import or Data Entry3. Data Organization4. Display the Code Book5. Conduct a Visual Data Check6. Descriptive Analysis of the Data.
About the author
Thomas W. MacFarland
Senior Research Associate and Associate Professor
Nova Southeastern University Office of Institutional Effectiveness
Fort Lauderdale, FL 33314 tommac@nova.edu
Summary
In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphicalfigures to complement outcomes from parametric Two-Way ANOVA.
Additional text
“This book provides a detailed description of the
use of R code with examples for statistical tests and graphics in two-way
analysis of variance in four chapters. … It is a great softcover book for
self-learning and self-training at a modest price.” (Subir Ghosh, Technometrics, Vol. 56 (4), November,
2014)
Report
"This book provides a detailed description of the use of R code with examples for statistical tests and graphics in two-way analysis of variance in four chapters. ... It is a great softcover book for self-learning and self-training at a modest price." (Subir Ghosh, Technometrics, Vol. 56 (4), November, 2014)
