 Optimizely Web Experimentation
 Optimizely Personalization
 Optimizely Performance Edge
 Optimizely Feature Experimentation
 Optimizely Full Stack (Legacy)
When you run experiments, Optimizely determines the statistical likelihood of each variation actually leading to more conversions on your metrics. This matters because when you look at your results, you are probably less interested in seeing how a variation compared to the baseline and more interested in predicting whether a variation will be better than the baseline when implemented in the future.
Optimizely’s Stats Engine powers statistical significance calculations. It uses an optimized statistical framework to run experiments with high statistical rigor while making it easy for anyone to interpret results. Specifically, Stats Engine lets you make business decisions on results as experiments are running, regardless of preset sample sizes and the number of goals and variations in an experiment.
As with all statistical calculations, it is impossible to predict a variation's lift with certainty. This is why the results page displays Optimizely's level of confidence. This way, you can make sophisticated business decisions from your results without needing an expert level of statistical knowledge.
How Stats Engine works
To learn about the nuts and bolts of how Stats Engine works and how to interpret the results it generates, review these articles:

Why Stats Engine results sometimes differ from classical statistics results

Why Stats Engine controls for false discovery instead of false positives
Statistical concepts and techniques
You may also find it useful to read about the statistical concepts and techniques Stats Engine uses:
Further reading
If you would like even more background on how Optimizely's Stats Engine works, here are a few resources:
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