It equally divides the distribution into four equal parts called quartiles. It is a better measure of dispersion than range because it leaves out the extreme values. Interquartile range gives another measure of variability. Sometimes it may happen that mean, median, and mode are same for both groups. Mean, Median and Mode for both the groups. You have already calculated the central tendency of your data i.e. Let’s think, in certain cases, you are comparing two groups. It is also commonly used in box plots to visualize the distribution of a data set. The IQR is often used as a measure of variability or spread in a data set, and is considered a robust statistic since it is less sensitive to outliers or extreme values than the range or standard deviation. Finally, the IQR is calculated as the difference between Q3 and Q1. Then, the median (Q2) of the data set is found, and the lower quartile (Q1) is the median of the lower half of the data set (i.e., the data points below the median), while the upper quartile (Q3) is the median of the upper half of the data set (i.e., the data points above the median). This makes it a preferable way to measure dispersion compared to a metric like the range, which simply tells us the difference between the largest and the smallest values in a dataset.To calculate the IQR, one must first arrange the data in order from lowest to highest. Since it only tells us the spread of the middle 50% of the dataset, it isn’t affect by unusually small or unusually large outliers. The nice part about using the IQR to measure spread is that it’s resistant to outliers. Some other ways to measure spread are the range, the standard deviation, and the variance. The interquartile range only represents one way of measuring the “spread” of a dataset. Note that we could also have found the interquartile range of the dataset in the previous example by using one formula: This tells us how spread out the middle 50% of the values are in this particular dataset. The IQR turns out to be 39.5 – 23.5 = 16. To find the interquartile range (IQR), we simply subtract Q1 from Q3: To find the third quartile, we type =QUARTILE(A2:A17, 3) into any cell we choose: To find the first quartile, we simply type =QUARTILE(A2:A17, 1) into any cell we choose: To find the IQR, we can perform the following steps: Suppose we would like to find the IQR for the following dataset: quart: the quartile you would like to calculate.array: the array of data you’re interested in.Microsoft Excel doesn’t have a built-in function to calculate the IQR of a dataset, but we can easily find it by using the QUARTILE() function, which takes the following arguments: How to Calculate the Interquartile Range in Excel This tells us how spread out the middle 50% of the values are in this dataset. Thus, the interquartile range (IQR) for this dataset is 91 – 75.5 = 15. The third quartile turns out to be 91 and the first quartile is 75.5. *Quartiles are simply values that split up a dataset into four equal parts.įor example, suppose we have the following dataset: It is calculated as the difference between the first quartile* (Q1) and the third quartile (Q3) of a dataset. The interquartile range, often denoted IQR, is a way to measure the spread of the middle 50% of a dataset. This tutorial explains how to calculate the interquartile range of a dataset in Excel.
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