This notebook demonstrates a common workflow for detecting and removing outliers from a dataset using the Interquartile Range (IQR) method. Outliers are data points that significantly deviate from the ...

and how to apply it in Python. IQR is a measure of how spread out the middle 50% of the data is. It is calculated by subtracting the first quartile (Q1) from the third quartile (Q3). The first ...

This is a part of project - II made for UCS633 - Data analytics and visualization at TIET. Z-SCORE : If the population mean and population standard deviation are known, the standard score of a raw ...

The \(\frac{3{(n+1)}}{4}\) value So the upper quartile (UQ) is 18. The interquartile range (IQR) is therefore 18 - 4 = 14. You will notice that the fact there is an outlier in this data (60 ...