Four sets of X,Y datapoints that have exactly (or very close) common statistical parameters (mean, variance, correlation, linear regression, R^2), but with vastly different spatial distributions and “behavior” when looked at visually.
It's little surprising that the author was doing perf work and not already comparing distributions. As the rest of the article outlines, you learn a lot more with more data!
It's complicated, but really worth learning how prometheus and grafana heatmaps combine if you want dashboards for real time service data. Multimodal distributions are basically the expected outcome given all the caching done in distributed systems.
https://en.wikipedia.org/wiki/Anscombe%27s_quartet
Four sets of X,Y datapoints that have exactly (or very close) common statistical parameters (mean, variance, correlation, linear regression, R^2), but with vastly different spatial distributions and “behavior” when looked at visually.
It's complicated, but really worth learning how prometheus and grafana heatmaps combine if you want dashboards for real time service data. Multimodal distributions are basically the expected outcome given all the caching done in distributed systems.