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The term 'quartiles' in statistics specifically refers to the division of a dataset into four equal parts. This means that when data is arranged in ascending order, each quartile represents a quarter of the data points. The three points that divide the dataset into these four parts are known as the first quartile (Q1), the second quartile (Q2, which is also the median), and the third quartile (Q3). Each quartile helps in understanding the spread and distribution of the data, allowing for comparisons and analysis of different segments of the dataset.

For instance, Q1 is the value below which 25% of the data falls, while Q3 indicates the value below which 75% of the data is found, providing key insights into the data distribution. Understanding quartiles is crucial for analyzing data sets effectively, especially in fields that require statistical analysis and data representation.