DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Data Mining Data Mining with Rattle Introduction Data Transform Explore A Model Building Framework Unsupervised Modelling Two Class Models Multi Class Models Regression Models Text Mining Evaluation and Deployment Moving into R Troubleshooting R for the Data Miner R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Cluster Analysis Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products AlphaMiner Borgelt Data Mining Suite KNime R Rattle Weka Closed Products C4.5 Clementine Equbits Foresight GhostMiner InductionEngine ODM Enterprise Miner Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Boxplot

A http://en.wikipedia.org/wiki/boxplotboxplot tukey:1977:eda (also known as a box-and-whisker plot) provides a graphical overview of how data is distributed over the number line. R's boxplot function displays a graphical representation of the textual summary of data. The skewness of the distribution of the data becomes clear.

A boxplot shows the http://en.wikipedia.org/wiki/medianmedian (the second http://en.wikipedia.org/wiki/quartilequartile or the 50th http://en.wikipedia.org/wiki/percentilepercentile) as the thicker line within the box ($Ash=2.36$). The top and bottom extents of the box ($2.558$ and $2.210$ respectively) identify the upper quartile (the third quartile or the 75th percentile) and the lower quartile (the first quartile and the 25th percentile). The extent of the box is known as the http://en.wikipedia.org/wiki/Interquartile_rangeinterquartile range ( $2.558-2.210=0.348$). The dashed lines extend to the maximum and minimum data points that are no more than $1.5$ times the interquartile range from the median. Outliers (points further than $1.5$ times the interquartile range from the median) are then individually plotted (at 3.23, 3.22, and 1.36). Our plot here adds faint horizontal lines to more easily read off the various values.

load("wine.Rdata")
attach(wine)
boxplot(Ash, xlab="Ash")
abline(h=seq(1.4, 3.2, 0.1), col="lightgray", lty="dotted")

http://rattle.togaware.com/code/rplot-wine-boxplot-single.R

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