![]() The number at this position is the second quartile. If n * (2 / 4) is not an integer, then round it up.If n * (2 / 4) is an integer, the second quartile is the mean of the numbers at positions n * (2 / 4) and n * (2 / 4) + 1.Tip: An integer is a whole number-it can be written without any numbers after the decimal place. The number at this position is the first quartile. If n * (1 / 4) is not an integer, then round it up.If n * (1 / 4) is an integer, then the first quartile is the mean of the numbers at positions n * (1 / 4) and n * (1 / 4) + 1.Sort the observations from smallest to largest. ![]() Count the number of observations in the dataset ( n).To find the quartiles of a dataset or sample, follow the step-by-step guide below. In a probability distribution, the quartiles divide the distribution’s range into four intervals with equal probability.In a sample or dataset, the quartiles divide the data into four groups with equal numbers of observations.The third quartile (Q3, or the upper quartile) is the 75th percentile, meaning that 75% of the data falls below the third quartile.īy splitting the data at the 25th, 50th, and 75th percentiles, the quartiles divide the data into four equal parts.The second quartile (Q2, or the median) is the 50th percentile, meaning that 50% of the data falls below the second quartile.The first quartile (Q1, or the lowest quartile) is the 25th percentile, meaning that 25% of the data falls below the first quartile.In general terms, k% of the data falls below the kth percentile. A percentile is a value with a certain percentage of the data falling below it. They summarize the central tendency and variability of a dataset or distribution. Quartiles are a set of descriptive statistics. Frequently asked questions about quartiles and quantiles.
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