I have a vector of positive integer counts taken from a time-series (365 observations/days).
I believe that there is variance in these counts due to the day of week they are observed and as I am looking for abnormal observations I'd like to remove this variance before placing a threshold on what is abnormal.
I have tried creating a vector of days (1-7) which goes from t1 to t365 and counting the activity on those days. I then divided each of the count observations by the activity for that day.
Is this the right approach and how do I measure the strength of the correlation?
(I have looked at point-biserial correlation but is that just for binary categories?)
Ultimately I would like to see how much of the variance in the discrete vector is explained by the day of the week.