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Qq Plot In R. You give it a vector of data and R plots the data in sorted order versus quantiles from a standard Normal distribution. Suppose if we are executing a statistical analysis the test comes under parametric methods assumes variable is Normally distributed we can make use of a Q-Q plot to check that assumption. To create the basic plot we can use the stat_qq function to calculate the quantiles and the stat_qq_line to calculate the line. For example consider the trees data set that comes with R.
You simply give the sample you want to plot as a first argument. QQ-plots in R first need to understand the Q-Q plot. A Q-Q plot compares the quantiles of two distributions so the qqplot function requires two arguments. It can make a quantile-quantile plot for any distribution as long as you supply it with the correct quantile function. Follow answered Feb 22 16 at 208. To create the basic plot we can use the stat_qq function to calculate the quantiles and the stat_qq_line to calculate the line.
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In R you can create the normal quantile-quantile plot using the qqnorm function. This function plots your sample against a normal distribution. The qqPlot function is a modified version of the R functions qqnorm and qqplot. Qqnorm creates a Normal Q-Q plot. Follow answered Feb 22 16 at 208. The easiest way to create a -log10 qq-plot is with the qqmath function in the lattice package.