Is IQR better for non-symmetrical data?
PLease
yes
The IQR (Interquartile Range) is a measure of statistical dispersion that is often used to describe the spread of a dataset. It is defined as the difference between the upper quartile (Q3) and the lower quartile (Q1).
The IQR is robust to outliers, meaning that it is less affected by extreme values in the dataset compared to other measures of spread like the range or standard deviation. This makes it particularly useful when dealing with non-symmetrical data or data sets that contain outliers.
To calculate the IQR, follow these steps:
1. Arrange your dataset in ascending order.
2. Find the median (Q2) of the dataset. If the dataset has an odd number of values, the median is the middle value. If the dataset has an even number of values, the median is the average of the two middle values.
3. Determine Q1, the first quartile. This is the median of the lower half of the dataset, excluding the median value if the dataset has an odd number of values.
4. Determine Q3, the third quartile. This is the median of the upper half of the dataset, excluding the median value if the dataset has an odd number of values.
5. Calculate the IQR by subtracting Q1 from Q3: IQR = Q3 - Q1.
In conclusion, the IQR is a useful measure of spread for non-symmetrical data as it is less influenced by outliers and extreme values.