What is the meaning of a statistically significant result in an A/B test?

• A. The observed difference could be due to random chance
• B. The results must be ignored
• C. The test results are guaranteed to improve performance
• D. The observed difference is unlikely to be due to random variation

Answer: (D)

In an A/B test, statistical significance means the observed difference between the two variants is unlikely to have happened by random variation alone, given the data and a chosen threshold for evidence. We test whether there is any real difference by using a p-value: if the p-value is below the pre-set level (often 0.05), we say the result is statistically significant and we reject the assumption that there is no difference.

This indicates there’s evidence of a real effect, but it doesn’t guarantee that the new variant will improve performance in the real world, nor does it say the difference is large or important in practical terms. It also doesn’t imply ignoring the results or that random chance completely explains them. Significance depends on factors like sample size and variability: bigger samples can reveal smaller differences as significant, while small samples might miss real effects.