A statistical hypothesis test determines if a significant difference exists between the means of two independent groups. This method relies on the t-distribution to evaluate whether the observed disparity is likely due to chance or reflects a real effect. For instance, it could be used to compare the effectiveness of two different teaching methods by analyzing the test scores of students taught using each method.
This approach is valuable in various fields, including medicine, engineering, and social sciences, for comparing outcomes or characteristics across separate populations. Its strength lies in its ability to infer population-level differences from sample data. Historically, this method provided a more accessible way to perform hypothesis testing before widespread computational power was available, relying on pre-calculated t-distribution tables.
