Visualizing data prior to any analysis is a basic and important step. Univariate plots are those that take into account one varible, these may include histograms, density plots, etc. Here there are som examples with the dataset airquality : HISTOGRAMS: Histogram is a very well-known univariate plot: hist(airquality$Wind) For the construction of the histogram a specific number of bins and their spacing in the horizontal axis is required. The number of bins can be set by the parameter breaks : par(mfrow = c(1,3)) hist(airquality$Wind, xlab = "Wind", col = "red", main=" Histogram Wind") hist(airquality$Wind, xlab = "Wind", col = "orange", main=" Histogram Wind", breaks= 20) hist(airquality$Wind, xlab = "Wind", col = "gold", main=" Histogram Wind", breaks= 40) For setting the axis limits: par(mfrow = c(1,2)) hist(airquality$Wind, xlab = "Wind", col = "red...
