Naive Analysis of Variance

Abstract

The Analysis of Variance is often taught in introductory statistics courses, but it is not clear that students really understand the method. This is because the derivation of the test statistic and p-value requires a relatively sophisticated mathematical background which may not be well-remembered or understood. Thus, the essential concept behind the Analysis of Variance can be obscured. On the other hand, it is possible to provide students with a graphical technique that makes the essential concept transparent. The technique discussed in this article can be understood by students with little or no background in probability or statistics. In fact, only the ability to add, subtract, compute averages, and interpret histograms is required.

Polycyclic aromatic hydrocarbons in water samples from a Nigerian bitumen seepage: Gas chromatography- mass spectrometry quantification

“…One-way analysis of variance (ANOVA) of the resulting PAHs and their maximum allowable concentrations water was carried out using SPSS (Braun, 2012). Correlation coefficient was used to compare concentrations of PAHs in water samples to their respective control samples at α = 0.05 level of significance.…”

Reinforcing Sampling Distributions Through a Randomization-Based Activity for Introducing ANOVA

“…A main reason for this is that students must have solid knowledge of numerous mathematical and statistical topics, including, but not limited to, sums of squares, variability, p-values, the Fdistribution, and hypotheses (Braun 2012). Previous research studies have investigated different approaches to effectively teach ANOVA (Sturm-Beiss 2005;Lesser and Melgoza 2007;Rossman and Chance 2008;Braun 2012). Both Sturm-Beiss and Rossman and Chance have developed applets for easy visualization of ANOVA.…”