Take the difference between these two observations and multiply it by the fractional portion of the rank.For our example, 8.4 falls between 8 and 9, which corresponds to the data values of 35 and 40. If the rank is not an integer, you need to interpolate between the two closest observations.If the rank in step 1 is an integer, find the data value that corresponds to that rank and use it for the percentile.For our example, to find the rank for the 70 th percentile, we take 0.7*(11 + 1) = 8.4.

Use: rank = p(n+1), where p = the percentile and n = the sample size. Calculate the rank to use for the percentile.To calculate an interpolated percentile, do the following: Consequently, a third approach interpolates between two data values. Depending on the nature and size of your dataset, this difference can be substantial. Definition 3: Using an Interpolation ApproachĪs you saw above, using either “greater” or “greater than or equal to” changes the results. Using the first two definitions, we have found two values for the 70% percentile-35 and 40. One-quarter of the values fall below the IQR while another quarter of the values are above it. The interquartile range represents the middle half of the data. Larger IQRs indicate that the data are more spread out. This range corresponds to the distance between the first quartile and the third quartile (IQR = Q3 – Q1). The interquartile range (IQR) is a measure of dispersion in statistics. The top quarter of the scores fall above this value, while three-quarters fall below it. The third quartile, also known as Q3 or the upper quartile, is the value of the 75% percentile.Half the scores are above and half below.

The second quartile, also known as Q2 or the median, is the value of the 50 th percentile.

The bottom quarter of the scores fall below this value, while three-quarters fall above it.

The first quartile, also known as Q1 or the lower quartile, is the value of the 25 th percentile.

Quartiles are values that divide your data into quarters, and they are based on percentiles. The median is a measure of central tendency in statistics. Half the values are below the 50 th percentile, and half are above it.

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