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# Quartile AnalyticsTrade Team Last updated on 26 Apr 2023

# Quartile

Quartiles are a type of statistical measure used to divide a set of data into four equal parts. Quartiles are used to measure the spread of a data set, and are calculated by dividing the data into four equal parts. The first quartile (Q1) is the median of the lower half of the data set, the second quartile (Q2) is the median of the entire data set, and the third quartile (Q3) is the median of the upper half of the data set. The interquartile range (IQR) is the difference between the third and first quartiles.

## History of Quartiles

The concept of quartiles was first introduced by the French mathematician Pierre-Simon Laplace in 1774. Laplace used quartiles to measure the spread of a data set, and to compare different data sets. Since then, quartiles have been used in a variety of fields, including economics, finance, and medicine. Quartiles are also used in the calculation of the five-number summary, which is a set of descriptive statistics used to summarize a data set.

## Table of Comparisons

Quartile Value
Q1 25th percentile
Q2 50th percentile (median)
Q3 75th percentile
IQR Difference between Q3 and Q1

## Summary

Quartiles are a type of statistical measure used to divide a set of data into four equal parts. Quartiles are used to measure the spread of a data set, and are calculated by dividing the data into four equal parts. The first quartile (Q1) is the median of the lower half of the data set, the second quartile (Q2) is the median of the entire data set, and the third quartile (Q3) is the median of the upper half of the data set. The interquartile range (IQR) is the difference between the third and first quartiles. For more information about quartiles, please visit websites such as Investopedia, Khan Academy, and Stat Trek.

• Median
• Mode
• Mean
• Range
• Standard Deviation
• Variance
• Five-Number Summary
• Box Plot
• Outliers
• Interquartile Range

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