These metrics attempt to identify where the exact 'middle' or 'typical' value of your dataset lives.

Depending on data skew, the Median is often a much safer representation of an average reality than the Mean formula.

Variance and Standard Deviation measure how wildly your numbers bounce away from the central Mean.

A massive standard deviation suggests highly chaotic data. A tiny standard deviation means almost every data point clusters right on top of the calculated Mean.

Quartiles systematically break your ordered data list into distinct 25% percentile slices.

By subtracting Q1 from Q3 to find the Interquartile Range (IQR), you can mathematically isolate the core 50% behavior trend, completely ignoring wild outlier spikes.