What type of test compares two different values of the same variable to determine the most effective one?

The best choice for this question is the Hypothesis A/B Test. This statistical method is specifically designed to compare two variations (A and B) to determine which one performs better or is more effective in relation to a specific outcome or metric.

In practice, an A/B test involves randomly assigning participants into two groups: one experiences variation A and the other experiences variation B. By measuring the performance of each variant against a common objective (such as conversion rates or user engagement), analysts can draw conclusions about which option is preferable based on the data collected.

While correlation tests focus on establishing relationships between two variables rather than comparing two instances of the same variable, and regression tests analyze relationships and predict outcomes based on one or more predictor variables, neither are specifically set up for direct comparative testing in the same way A/B testing is. Comparative analysis, while it indicates a general method of evaluating different variables, does not inherently define the structured approach and metrics used in an A/B test. Hence, Hypothesis A/B Test is the most accurate answer for determining the effectiveness of two different values of the same variable.