This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started....
Aegyptin is a 30 kDa mosquito salivary gland protein that binds to collagen
and inhibits platelet aggregation. We have studied the biophysical properties
of aegyptin and its mechanism of action. Light-scattering plot showed that
aegyptin has an elongated monomeric form, which explains the apparent
molecular mass of 110 kDa estimated by gel-filtration chromatography.
More important is the scatter plot of data points, each representing a microfinance
institution. Many points are above the threshold for profitability, and many are on the left of the
graph, indicating low reliance on soft (subsidized) funds. This is the hope of commercial
microfinance. But note too that an ample number of institutions are above the threshold and to
the right, funded by social investors of various stripes. The solid circles represent institutions
with for-profit status, while the empty circles are non-profits.
Chapter 8 – Correlation and regression. After studying this chapter you will be able to understand: Define and interpret a scatter plot, calculate and interpret a sample covariance, calculate and interpret a sample correlation coefficient, explain how outliers can affect correlations,...
Chapter 4 - Describing data: Displaying and exploring data. When you have completed this chapter, you will be able to: Develop and interpret a dot plot; develop and interpret a stem-and-leaf display; compute and understand quartiles, deciles, and percentiles; construct and interpret box plots; compute and understand the coefficient of skewness; draw and interpret a scatter diagram; construct and interpret a contingency table.
Chapter 4 - Describing data: Displaying and exploring data. After studying this chapter you will be able to: Construct and interpret a dot plot, identify and compute measures of position, construct and analyze a box plot, compute and describe the coefficient of skewness, create and interpret a scatter diagram, develop and explain a contingency table.