����app

Quartiles are values that divide a dataset into four equal parts, each containing 25% of the data. The first quartile (Q1) marks the 25th percentile, the second quartile (Q2) is the median or 50th percentile, and the third quartile (Q3) represents the 75th percentile. Understanding quartiles helps in analyzing the spread and central tendency of data.

Percentiles are measures that indicate the relative standing of a value within a dataset, dividing the data into 100 equal parts. For example, the 30th percentile is the value below which 30% of the data falls. Percentiles are useful for comparing scores or measurements across different datasets, providing insights into distribution and ranking.

The relationship between quartiles and percentiles is that quartiles are specific percentiles. Each quartile corresponds to a specific percentile: Q1 is the 25th percentile, Q2 is the 50th percentile, and Q3 is the 75th percentile. This connection allows for a deeper understanding of data distribution, as quartiles provide a more concise summary of the data's spread while percentiles offer a more granular view.