This chapter discusses the Gini index and the Gini mean difference, two closely related statistics that have vastly different applications. These applications include traditional ones such as income and wealth, as well as nontraditional ones arising in such diverse fields such as digital imaging, genetics, and astronomy. The Gini index and the Gini mean difference are defined in terms of the Lorenz curve. The Lorenz curve allows the development of a geometric intuition regarding the quantities involved. The curve also provides an interesting perspective on how the Gini index and the Gini mean difference change under various scenarios involving income inequality in a country. The Lorenz curve and Gini’s two measures are further explored in the context of measuring contrast in grayscale images. The coefficient of variation and standard deviation are discussed for the sake of comparison, and several other measures of spread and inequality arising in the Lorenz curve are also noted.