Previously, we discussed how to apply the most basic hypothesis test: the z-test. It requires a relatively large sample size, and might be appreciated less by hackers searching for truth on a tight budget of time and money.
As an alternative, we briefly mentioned the t-test. The basic procedure still applies: form hypotheses, sample data, check your assumptions, and perform the test. This time though, we’ll run the test with real data from IoT sensors, and programmatically rather than by hand.
The most important difference between the z-test and the t-test is that the t-test uses a different probability distribution. …read more
Continue reading Statistics and Hacking: A Stout Little Distribution→