2. Data. visualization Most of the time, the information in the data set is also well captured graphically. Histogram, scatter plot, boxplot, QQ plot are frequently used tools for data visualization. Use ggplot for all of these visualizations. (a) Produce a histogram of mmPH with the title 'Histogram of meH' based on algae data set. Use an appropriate argument to show the probability instead of the frequency as the vertical axis. (Hint: look at the examples in the help le for function geom_histogram()). Is the distribution skewed? (b) Add a density curve using geom_density() and rug plots using geom_rug() to above histogram. (c) Create a boxplot with the title 'A conditioned Boxplot of Algal 051' for al grouped by size. (Refer to help page for geom_boxplot O ). (d) Are there any outliers for N03 and N H 4? How many observations would you consider as outliers? How did you arrive at this conclusion? e Com are mean & variance vs. median & MAD for N 03 and N H 4. What do ou notice? Can ou P Y y conclude which set of measures is more robust when outliers are present