These docs are for v1.0. Click to read the latest docs for v2.0.

How Experiment Statistics are Calculated

Taplytics uses two methods to calculate the effectiveness of goals created to evaluate your experiments:

  • Z-Score - is used for binary conversion goals i.e. button clicks / app sessions goals

  • Two-Tailed T-Test - is used for value optimization goals where the comparison is the difference between two average values

Both methods test for a 95% confidence level.


Below is a brief definition the calculations use to determine the success of each type of goal when viewing the Experiment Results page on the Taplytics Dashboard:

Binary Conversion Goals

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Conversion Rate
This is a straight calculation of the number of conversion events divided by the number of events you've chosen to be the denominator, most commonly this is app session.

% Change
This is calculated in the following way:

(Conversion Rate Variation - Conversion Rate Baseline) / Conversion Rate Baseline

Projected Variance
This is calculated using standard methods for z-scores.

Chance of Beating Baseline
This number will fluctuate as your experiment accumulates more data.

Once the Chance of Beating Baseline reaches 100% it confirms that the variation has reached a 95% confidence between Baseline and Variation.

Value Optimization Goals

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Event Average
Is the calculated mean of the event average.

Percentage Change
This number is calculated below:

(Event Average Variation - Event Average Baseline) / Event Average Baseline

Chance of Beating Baseline
Similar to above - this number will fluctuate as your experiment accumulates more data.

Once the Chance of Beating Baseline reaches 100% it confirms that the variation has reached a 95% confidence between Baseline and Variation.