Quintiles

A quintile divides a data set into five equal parts. Each quintile represents 20% of the observations: the first quintile is the lowest 20%, the second is the next 20%, and so on up to the fifth (top) quintile.

Key takeaways

• Quintiles split data into five equal groups (each 20%).
• They are useful for analyzing large populations or distributions (e.g., incomes, test scores, prices).
• Alternatives include tertiles (3 parts) and quartiles (4 parts); percentiles provide finer granularity.
• Comparing mean and median helps identify skew or outliers within quintiles.

How quintiles work

1. Sort the data from smallest to largest.
2. Identify cutoff points at the 20th, 40th, 60th, and 80th percentiles.
3. Each interval between cutoffs is one quintile.

Example: For a year of daily closing prices of a stock, the top 20% of closing prices form the fifth quintile and the bottom 20% form the first quintile. Outliers can shift the mean, so examining quintile distributions helps reveal where values cluster and whether the data are skewed.

Common uses

• Income and wealth distribution analysis (e.g., demonstrating how income is distributed across society).
• Policy debates (e.g., arguments about tax burdens or subsidies often reference quintiles).
• Public health, education, and social science research to compare groups across a population.
• Market and financial analysis to segment observations (prices, returns) and identify extremes.

Alternatives and related measures

• Tertiles: divide data into three equal groups (useful for smaller samples).
• Quartiles: divide data into four equal groups; commonly used in box plots.
• Percentiles: divide data into 100 parts for finer detail.
• Mean vs. median: comparing these indicates skew—mean > median suggests top-heavy data; mean < median suggests bottom-heavy data.

FAQs

• What is the fifth quintile?
• The fifth quintile is the top 20% of the data distribution.
• What is a tertile?
• A tertile divides data into three equal parts (each ~33.3%).
• When should I use quintiles instead of quartiles or percentiles?
• Use quintiles for broad segmentation of large data sets. Use quartiles or percentiles for smaller samples or when more/finer granularity is needed.

Bottom line

Quintiles are a simple, effective way to divide a distribution into five equal parts to analyze where observations fall within a population. They are widely used in economics, public policy, and research to summarize and compare groups, but should be interpreted alongside measures like mean and median to account for skew and outliers.