Mastering Data-Driven A/B Testing: Precise Sample Size Calculation and Ensuring Statistical Significance
One of the most critical yet often misunderstood aspects of effective A/B testing is determining the appropriate sample size to achieve statistically significant results. Without precise calculation, tests may either run too long, wasting resources, or prematurely declare winners based on insufficient data. This deep-dive addresses the technical intricacies of sample size calculation, how to …