# Conversion rates over time

I'm looking at some data conversion rates for an ad over time.

          view      clicks
Day 1      100       10
Day 2      150       13
Day 3      90        9
Day 4      130       20
Day 5      150       21


Given that there is quite a bit of variation in the conversion rate of the ad from day to day, I want to know the confidence interval for the conversion rate across the 5 days. For each day I could develop confidence intervals for the conversion rate, and then compare across the days. However, I'm just not sure how to know with 90% confidence that the confidence interval for all the days was between so and so. Can anyone help!

In R, I can calculate the confidence intervals for two seperate ads using the following function:

abtestfunc <- function(ad1, ad2){
minmax1 = c((ad1 - 1.96*sterror1) * 100, (ad1 + 1.96*sterror1) * 100)
minmax2 = c((ad2 - 1.96*sterror2) * 100, (ad2 + 1.96*sterror2) * 100)
print( round(minmax1,2) )
print( round(minmax2,2) )
}


Or is it right to calculate the means conversion rate for the conversion rates and then develop conf intervals. Then compare whether the majority of days fall within the conversion rate.