When a data set has outliers or extreme values, we summarize a typical value using the median as opposed to the mean. When a data set has outliers, variability is often summarized by a statistic called the interquartile range , which is the difference between the first and third quartiles. The quartiles can be determined following the same approach that we used to determine the median, but we now consider each half of the data set separately. The interquartile range is defined as follows:.
How to Remove Outliers in R | R-bloggers
The quartiles of a ranked set of data values are three points which divide the data into exactly four equal parts, each part comprising of quarter data. Uses 1. Unlike range, IQR tells where the majority of data lies and is thus preferred over range. IQR can be used to identify outliers in a data set.
How to Find the Interquartile Range in R
In order to calculate the IQR, we need to begin by ordering the values of the data set from the least to the greatest. Likewise, in order to calculate the median, we need to arrange the numbers in ascending order i. Now, let's perform this task with another example data set that is comprised of an even number of values.
The results of your statistical analyses help you to understand the outcome of your study, e. Statistics are tools of science, not an end unto themselves. Statistics should be used to substantiate your findings and help you to say objectively when you have significant results. Therefore, when reporting the statistical outcomes relevant to your study, subordinate them to the actual biological results.