I am curious to find out the confidence level of results. It's best to give an example of what I mean cause I struggle to speak in the technical terms.
Example: Jack runs an advertisement that 1000 people see. 10 of those people convert and actually purchase something. Jack is sure his conversion rate is 1%.
Sally disagrees. She thinks Jack doesn't have enough of a statistical confidence level in this result. What is the confidence level of 1% being the result.
A formula to get that would be great.
EDIT: I'm trying to add a statistical element to my marketing for my business. I plan to run a lot of advertisements so am trying to find a way to understand how many results I need to collect before I can prove or disprove a hypothesis I am testing.
Let's say for example my hypothesis is that running a certain ad will result in a conversion rate of 3% of people clicking the ad overtime.
For now, let's say I have just started the experiment and out of 1000 people, 30 did click it. So it seems that the the conversion rate (or probability of a person click the ad) is 3% (0.03 in probability).
However, I shouldn't trust these results because the sample size is too small. Instead I want to know what is probability that 3% (+ or - a margin of error) is indeed the conversion rate?
I thought I'd have to use a confidence intervals but now I'm thinking I should probably something that involves variance. I'll do some more research and update this when I find more. If you have any thoughts in the mean time on how to solve this problem, please let me know. Much obliged.