This is the result of running Descriptive Statistics from some data I made up
<TABLE style="WIDTH: 116pt; BORDER-COLLAPSE: collapse" border=0 cellSpacing=0 cellPadding=0 width=154><COLGROUP><COL style="WIDTH: 68pt; mso-width-source: userset; mso-width-alt: 3291" width=90><COL style="WIDTH: 48pt" width=64><TBODY><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: windowtext 0.5pt solid; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 116pt; HEIGHT: 15pt; BORDER-TOP: windowtext 1pt solid; BORDER-RIGHT: #f0f0f0; mso-ignore: colspan" class=xl65 height=20 width=154 colSpan=2 align=middle>Column1</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20></TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0"></TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Mean</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>4.785714</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Standard Error</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>0.621754</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Median</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>4.5</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Mode</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>2</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Standard Deviation</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>2.326389</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Sample Variance</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>5.412088</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Kurtosis</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>-1.02413</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Skewness</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>0.38752</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Range</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>7</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Minimum</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>2</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Maximum</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>9</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Sum</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>67</TD></TR><TR style="HEIGHT: 15.75pt" height=21><TD style="BORDER-BOTTOM: windowtext 1pt solid; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15.75pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" class=xl64 height=21 align=left>Count</TD><TD style="BORDER-BOTTOM: windowtext 1pt solid; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" class=xl64 align=right>14</TD></TR></TBODY></TABLE>
Just click on data analysis tools and select descriptive statistics & select your data - you need to check the descriptive statistics box to get the above table
This describes your data
You can then use various statistical functions in Excel to determine things you might be interested in
Say your mean for visits in a day is 95 and teh Standard deviation is 6.2
If you wanted teh probability that you would get fewer than 100 visists in any day you would use
NORMDIST(100,95,6.2,TRUE) which gives you 0.79 - there is a 79% probability that you wil get fewer than 100 visits on any day or a 1-0.79 (21%) probaility of getting more than 100 and so on
You can also do a CHI Squared test to look at the hypothesis that all days are the same in this case you compute a CHI Squared statistic
you make a range which looks like this with the average visits for each day of the week compared with what you expect (in this case that 1/5 of visits happen on each day):
<TABLE style="WIDTH: 288pt; BORDER-COLLAPSE: collapse" border=0 cellSpacing=0 cellPadding=0 width=384><COLGROUP><COL style="WIDTH: 48pt" span=6 width=64><TBODY><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 width=64></TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" width=64 align=left>mon</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" width=64 align=left>tues</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" width=64 align=left>wed</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" width=64 align=left>thur</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; WIDTH: 48pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" width=64 align=left>fri</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Actual</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>95</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>99</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>100</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>95</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>95</TD></TR><TR style="HEIGHT: 15pt" height=20><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; HEIGHT: 15pt; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" height=20 align=left>Expected</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>96.8</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>96.8</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>96.8</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>96.8</TD><TD style="BORDER-BOTTOM: #f0f0f0; BORDER-LEFT: #f0f0f0; BACKGROUND-COLOR: transparent; BORDER-TOP: #f0f0f0; BORDER-RIGHT: #f0f0f0" align=right>96.8</TD></TR></TBODY></TABLE>
Use the function CHITEST for this - it is 0.99
This gives you a number which is teh probability that actual deviated from the expected by chance - in this case there is a high probability (99%) that the values deviate by chance
But if you change the actual value for Wednesdays in my example to say 200 the CHITEST gives you a very small number (2.96E-15) which says there is a very small probability that this is chance and not related to the day of the week
Depending on what values you get you might want to look at each day separately and look at the probabilities for each day - maybe you get more visits on a monday or something so you might want to say "30% of visits happen on Monday" or "on 95% of Mondays we get more than 130 visits" or something like that.
You could do similar analysis for different weeks or quarters - maybe the first week of the month has more activity or something. In each case you need to set up your data that gives you what you would expect if the visits were random so you could look at 1/12th in each month compared to the actuals and run your CHI SQUARED test
As a first step I would plot all your data out to see if there is a pattern to it - weekly or monthly or whatever before testing it