1. Univariate Graphs III Review Create histogram from Commands Window. Multipanel histogram. Quantile Plots Quantile-Normal Plots Quantile-Quantile Plots

2. Histogram from Commands From the Command Window type graphsheet(height=6.4,width=7.5) hist(iris$sepal.length, nclass=10, xlab="sepal.length") Graphs from the Commands Window are fixed unless… Right click on the histogram and select Convert to Objects. Now you can change the axis scales, etc.

4. Multipanel Histogram In the Iris data window, select sepal.length and then CTRL select variety. Using the Graph->Multipanel menu, plot a Histogram. Note that under Conditioning Columns, the column list is variety Try changing the number of rows and columns in the layout to be 2 by 2

7. Multipanel Histogram for Several Variables In the Iris data window, select sepal.width and then CTRL select variety. Using the Graph->Multipanel menu, plot a Histogram. Select the same Graphsheet as was used for the previous histogram

10. Quantile Plots A Quantile Plot graphs the value of each observation against the fraction of observations that are equal to or less than that observation where i is the index of the observation in a sorted list from i = 1 to N

11. Quantile Plot of Sepal Length graphsheet(height=6.4,width=6.4) tLength <- length(iris$sepal.length) plot(c(1:tLength)/tLength, sort(iris$sepal.length), xlab = "Fraction Value", ylab="Sepal Length (cm)")

13. Quantile Plot of Sepal Length graphsheet(height=6.4,width=6.4) qqmath(~ sepal.length, distribution=qunif, data=iris, aspect=1, xlab = "Fraction Value", ylab="Sepal Length (cm)")

15. Quantile Plot of Sepal Length graphsheet(height=4,width=7.5) qqmath(~ sepal.length | variety, distribution=qunif, data=iris, panel = function(x, y) { panel.grid() panel.xyplot(x, y) }, layout=c(3,1), aspect=1, xlab = "Fraction Value", ylab="Sepal Length (cm)")

17. Quantile-Normal Plot Using Menus In the Iris data window, select sepal.length. Using the Graph->2D menu, select a Q-Q Plot. Right click on the graph, select Position/Size and then set the Aspect Ratio to 1.

19. Quantile-Normal Plot graphsheet(height=6.4,width=6.4) qqnorm(iris$sepal.length, xlab = "Quantiles from Normal Distribution", ylab = "Quantiles from Sample")

21. Quantile-Normal Trellis Plot graphsheet(height=6.4,width=6.4) qqmath(~ sepal.length, distribution=qnorm, data=iris, prepanel = prepanel.qqmathline, panel = function(x, y) { panel.qqmathline(y, distribution = qnorm) panel.qqmath(x, y) }, aspect=1, xlab = "Normal Distribution", ylab="Sepal Length (cm)")

23. Quantile-Normal Trellis Plot graphsheet(height=6.4,width=6.4) qqmath(~ sepal.length | variety, distribution=qnorm, data=iris, prepanel = prepanel.qqmathline, panel = function(x, y) { panel.qqmathline(y, distribution = qnorm) panel.qqmath(x, y) }, aspect=1, layout=c(2,2), xlab = "Normal Distribution", ylab="Sepal Length (cm)")

25. Quantile-Quantile Plot Using Menus In the Iris data window, select sepal.length. CTRL select petal.length Using the Graph->2D menu, select a Q-Q Plot. Right click on the graph, select Position/Size and then set the Aspect Ratio to 1.

27. Quantile-Quantile Trellis Plot graphsheet(height=6.4,width=6.4) qq(variety ~ sepal.length, data=iris, subset = variety=="Setosa" | variety=="Versicolor", aspect=1)

29. For Thursday Read A Tour of Trellis Graphics pp 1-17 (download from the following web page) http://cm.bell-labs.com/cm/ms/departments/ sia/project/trellis/software.writing.html Reaction papers are due October 3rd.