A statistical procedure evaluates whether there is enough evidence to conclude that the means of two populations are different. This involves formulating null and alternative hypotheses, selecting a significance level, calculating a test statistic, and determining a p-value. For example, a researcher might use this method to investigate if a new teaching method results in significantly higher test scores compared to the traditional method.
This approach is critical in various fields, allowing for data-driven decision-making and informed conclusions. It provides a rigorous framework for comparing two groups, enabling researchers and practitioners to assess the effectiveness of interventions, the differences between populations, or the impact of various factors. Historically, the development of these statistical tests marked a significant advancement in the ability to analyze and interpret data, moving beyond simple observation to quantitative comparison.
