Test Stats Aggregators

Make sure to include extension in order to use these aggregators.

Please refer to and http://www.ucs.louisiana.edu/~jcb0773/Berry_statbook/Berry_statbook_chpt6.pdf for more details.

z = (p1 - p2) / S.E. (assuming null hypothesis is true)

S.E. = sqrt{ p1 * ( 1 - p1 )/n1 + p2 * (1 - p2)/n2) }

(p1 – p2) is the observed difference between two sample proportions.

• : calculate the z-score using two-sample z-test while converting binary variables (e.g. success or not) to continuous variables (e.g. conversion rate).

Please note the post aggregator will be converting binary variables to continuous variables for two population proportions. Specifically

p2 = (successCount2) / (sample size 2)

pvalue2tailedZtest post aggregator

Example Usage

In this example, we use zscore2sample post aggregator to calculate z-score, and then feed the z-score to pvalue2tailedZtest post aggregator to calculate p-value.

A JSON query example can be as follows: