Thanks for the clarification. Should have been less lazy and reviewed the previous articles in this series. I understand the statistical difference underpinning the two approaches, now.
I think I’m still getting caught up on the difference between an experiment and a change in process. I first assumed that SPC was more to monitor a process for changes (essentially to keep it in the lane, and be able to respond quickly if out of band). So the method appears reactive instead of proactive.
So my confusion for this chart was that it looks like we’re trying to tell if changing a process has a statistically significant difference:
But still not sure when to use which when trying to improve a given metric. Am I running an experiment or am I changing a process? Is the major difference the existence of a control group?
The point about multiple distributions is a great one. Immediately I start to think about isolating each distribution, but this is likely impossible unless we change one potential source of distribution at a time.