A short spoken segment from a YouTube video by Kosta Ouzas explaining differences between quantiles/median and the arithmetic mean. The speaker gives an intuition: the median (a quantile) reflects central position less affected by peaks, while the average is pulled toward areas with many values (peaks/outliers) because it weights all observations equally.
Quantile gives us the median. The median is more like. Think about where you take the small smallest values, ice values of this deviation and then you find kind of the needle, the average gives way to how many data points that are close to, you know, these values, right? If you have a lot of value here, it will give more weight to these values, right? This is why the average is a little bit shifted towards it's higher than the median, because these peaks give a lot of weight to the average, right?
