If we suppose these are 22 iid samples from a Poisson then the max likelihood estimate for the Poisson parameter is 0.82 (the sample mean). Simulating such draws from such a Poisson and looking at sample correlation between Jan 15-Feb 4 and Jan 16-Feb 5, the p-value is 0.1. And when testing Poisson-ness vs negative binomial clustering (with the same mean), the locally most powerful test uses statistic (x-1.32)^2, and gives a simulated p-value of 0.44.
Echoing the others:
If we suppose these are 22 iid samples from a Poisson then the max likelihood estimate for the Poisson parameter is 0.82 (the sample mean). Simulating such draws from such a Poisson and looking at sample correlation between Jan 15-Feb 4 and Jan 16-Feb 5, the p-value is 0.1. And when testing Poisson-ness vs negative binomial clustering (with the same mean), the locally most powerful test uses statistic (x-1.32)^2, and gives a simulated p-value of 0.44.