What is the primary purpose of statistical tests in A/B testing?

• A. To schedule experiments
• B. To measure brand loyalty
• C. They determine which of the two options is more effective based on the data collected
• D. To determine the cheaper option

Answer: (C)

The main idea is using data-driven statistics to decide which variant performs better. In an A/B test, you collect outcomes from users shown either version and compare them on a predefined success metric, such as conversion rate or revenue per user. The statistical test asks whether any observed difference is likely real or just due to random fluctuations. By computing measures like p-values or confidence intervals and applying a chosen significance level, you determine which variant is more effective with a stated level of certainty. This focus on evidence-based performance is what sets the decision apart from simply scheduling experiments, measuring brand loyalty, or choosing the cheaper option, which are about logistics, different goals, or cost rather than the proven effectiveness of each option.