A statistical library for A/B testing (Version 1.02 Updated April 24, 2015).
You can embed abstats.js in your project or run commands right in the browser console. No programming knowledge required. To use it in the browser, just visit this calculator page, which has the library already loaded. All you need to do is open the browser console and run any of these commands.
interval_binary()
Calculate Adjusted Wald Confidence Interval with
interval_effect_binary()
Calculates Adjusted Wald Confidence Interval around the relative % difference in proportions
interval1_effect_binary()
Calculates 1-tailed Adjusted Wald Confidence Interval around the relative % difference in proportions
interval_effect_expected_binary()
Calculates predicted interval for relative increase
p_effect_false_binary()
Calculates probability of getting an effect size by chance.
confidence_binary()
Gives confidence that the difference between proportions is greater than 0
significance_binary()
Calculate p-value
sampleSize_binary()
Get sample size for binomial proportion
effect_binary()
Get minimum effect for fixed sample size. It's the same as sampleSize_binary() but solved for effect size.
sensitivity_binary()
Get expected power given a fixed sample size and desired effect. It's the same as sampleSize_binary() but solved for power pct.
interval_continuous()
Get confidence intervals for continuous data
significance_continuous()
Get p-value given 2 data sets of continuous data (e.g., revenue, time)
sampleSize_continuous1
Estimate sample size PER VARIATION for continuous data using current sample of data
sampleSize_continuous2
Estimates sample size PER VARIATION for continuous data using average and variance
normalDist()
Returns percentage (y axis) on Standard Normal Curve given z (x axis)
normalDistInv()
Figures out the z value (x) that yields a given percentage (y). It's the inverse of normalDist()
normalAreaZToPct()
Gives p-value form z score: calculates area under Standard Normal Curve from -z to z
normalAreaPctToZ()
Gives the 2-tailed z value such that the area under the Standard Normal Curve between -z and z is pct%. It's the inverse of normalAreaZToPct()
normalAreaZToPct_left()
Gives the left-tailed z value such that the area under the Standard Normal Curve between -z and z is pct%
normalAreaPctToZ_left()
Gives the left-tailed z value such that the area under the Standard Normal Curve between -z and z is pct%. It's the inverse of normalAreaZToPct_left()