I have some views per day of week data.  It's something like:Mondays: 100k viewsTuesday: 110k viewsWednesday: 140k views...Sunday: 80k viewsSo naively, it seems like Wednesday is a better day for website traffic.  However, I also understand that it's possible these differences are attributable to variance (maybe each day has an equal probability of getting a given viewer).How would I determine that Wednesday (for instance) is a better day for website traffic in a statistically significant fashion?Happy to clarify if this question is unclear.Thanks!
Determining Statistically Significant Differences in Views per Day of Week?
statistics;probability
First, you need a sample of the views data per day, that is:views in Mondays: 120, 111, 90, 150, ..views in Tuesdays: 50, 50, 57, 21, .....views in Sundays: 201, 184, 126, 191, ..These are random variables. Let's refer to them as $V_d$, where $d$ is the week day, e.g. $V_{monday}$. With those data, one option is to perform a hypothesis test.Depending on the distribution of $V_d$, you may do different things. If they are normal (which can be also tested by means of a hypothesis test) (so that $V_d \sim \mathcal{N}(\mu_d, \sigma_d)$), you can compare the means of two days, having a null hypothesis $H_0: \mu_{wednesday}  = \mu_{sunday}$ and the alternative hypothesis $H_1: \mu_{wednesday}  > \mu_{sunday}$ and choose an appropriate two sample test (depending on the variances of the distributions, sample size, etc).If your distributions are not gaussian, you may use a Kolmogorov-Smirnov test or a Mann-Whitney U test. To know how to choose between them, you can check this.