Description: A quartile is a type of quantile that divides an ordered data set into four equal parts. This means that by ranking the data from lowest to highest, quartiles allow us to identify the points that separate this data into four segments, each containing approximately 25% of the data. Quartiles are fundamental in statistical analysis as they provide a clear view of data distribution, enabling analysts to better understand the variability and central tendency of a data set. There are three main quartiles: the first quartile (Q1), which represents the lower 25% of the data; the second quartile (Q2), which is the median and divides the set into two equal halves; and the third quartile (Q3), which represents the lower 75% of the data. Understanding quartiles is essential for performing more complex analyses, such as calculating the interquartile range, which measures data dispersion and helps identify outliers. In summary, quartiles are key statistical tools that facilitate data interpretation and informed decision-making across various disciplines, from economics to scientific research.
