# Probability of webpage accessed in a particular hour

I want to programatically calculate at which particular hours of a day the probability of a webpage hits(accessed) are high.

Which statistic formula should I use to calculate the peak hours of the web page, if I have already the below data about a page .

e.g. for page xyz, at left I have hours and at right I have hits , For different pages the hits are different.

Page xyz hits count data:

hr=hits
1=0
2=0
3=0
4=0
5=14
6=0
7=0
8=5
9=5
10=8
11=10
12=10
13=12
14=7
15=5
16=5
17=3
18=0
19=0
20=0
21=0
22=0
23=0
24=0

• The data already give you the peak hours. What exactly are you looking for that you don't already have? Commented Mar 7, 2014 at 7:25
• What I want to do is to calculate the threshold value from this data. and if for each particular hour the number of hits exceed from this threshold value then that I will declare that hour as peak hour. So how to calculate the threshold value. Currently I am calculating the threshold value as: total number of hits/24 hrs. e.g. if total hits are 100 then 100/24 =4.16 So for any hour if hits are more that 4.16 then that hour is declared as peak hour otherwise not peak hour. I am computer student and weak in statistic. If there is better way to do it statistically then please guide me. Thanks. Commented Mar 7, 2014 at 7:45
• Which ones do you consider peak hours in this example? (5, 11, 12 and 13?)
– Matt
Commented Feb 9, 2015 at 10:13
• This is a Poisson process. You count the number of visits in a given time interval (per hour). See the following link on Why is the Poisson distribution chosen to model arrival processes in Queueing theory problems? at first instance. Commented Nov 1, 2015 at 8:55