Aderit A/B Statistical Analysis Calculat
Aderit Internet Marketing Consulting -- www.Aderit.com Directions: Use this calculator to determine the statistical degree of difference between two test cells. Typical analyses are to determine statistical differences in conversion rates or response rates. Enter your data in the grey boxes.
Response Rate Analysis Impressions Clicks Clickthrough Rate =
Test Cell A Conversion Rate Analysis 203 Clicks 4 Conversions 1.97% = Conversion Rate
Response Rate Analysis Impressions:
Clickthrough Rate =
Confidence Level
90%
This is how confident you are that there will be a long-term difference between the two clickthough or response rates.
How Confident Should You Be?
If you studied social science statistics in school they told you that you need confidence. That's what it takes to get published in an academic journal. This calculator is for business purposes. It's entirely up to you how confide be to choose one over another. However, Aderit's general advice is that if at least 80% confident you really should try to get more data. But, your circ may call for making a decision on less data. That's business.
Uses for this Calculator
This calculator is useful for tests of statistical significance for a variety of di The way it is described here is specific to A/B testing for PPC search engin technique is applicable to a wide variety of testing situations, such as direc offer, telemarketing, or other marketing medium.
0.014469 9.52E-05 2.73E-05 0.011064 1.307689 std dev.
al Analysis Calculator
two test cells. or response rates.
sponse Rate Analysis Impressions: Clicks: Clickthrough Rate =
Test Cell B Conversion Rate Analysis 191 Clicks 1 Conversions 0.52% = Conversion Rate
e will be a long-term or response rates.
n school they told you that you needed 95% published in an academic journal. s. It's entirely up to you how confident you need to ver, Aderit's general advice is that if you are not d try to get more data. But, your circumstances data. That's business.
istical significance for a variety of direct marketing problems. to A/B testing for PPC search engine advertising, but the y of testing situations, such as direct mail, email, landing page