Hanging Rootogram
- A hanging rootogram displays a distribution using vertically arranged bars whose heights correspond to frequency.
- Its vertical orientation makes it easy to compare relative frequencies and spot common values or outliers.
- It can be created from a table that maps values (rows) to their counts (columns).
Definition
Section titled “Definition”A hanging rootogram is a type of data visualization tool used to represent and analyze the distribution of a particular set of data. It is similar to a histogram, but instead of the bars being placed side-by-side, they are positioned one above the other, with the tallest bar representing the most frequent data value and the shortest bar representing the least frequent data value.
Explanation
Section titled “Explanation”The hanging rootogram uses a vertical arrangement of bars to convey frequency information. Because bars are stacked vertically, viewers can readily compare the heights to determine which values occur most or least often. This orientation is intended to provide a more intuitive understanding of the distribution and to make patterns, trends, and outliers easier to identify.
Examples
Section titled “Examples”Exam scores distribution
Section titled “Exam scores distribution”One example is analyzing the distribution of exam scores for a class. The data can be organized into a table with the exam scores as the rows and the number of students who received that score as the columns. That table can be used to create a hanging rootogram, with exam scores represented on the x-axis and the number of students who received each score represented on the y-axis. The resulting graph shows how the exam scores are distributed and helps identify the most common scores and any outliers.
Income distribution in a community
Section titled “Income distribution in a community”Another example is analyzing the distribution of income levels in a community. The data can be organized into a table with income levels as the rows and the number of households with each income level as the columns. That table can be used to create a hanging rootogram, with income levels on the x-axis and the number of households on the y-axis. The resulting graph shows the income distribution and can reveal income disparities and potential areas for intervention.