Abstract: Hypothesis testing serves as a fundamental component in analytical chemistry education for developing students' data processing skills and statistical reasoning. However, current textbooks predominantly emphasize independent two-sample t-tests while providing inadequate systematic coverage of paired t-tests. This pedagogical gap often leads to students' inappropriate application of statistical methods when analyzing grouped data, ultimately affecting their judgment of analytical result reliability. Using the classic environmental analysis case of comparing chloride concentrations between surface and bottom lake water, this study systematically contrasts the principles, application conditions, and computational procedures of independent versus paired t-tests. By clarifying their fundamental statistical differences and selection criteria, we aim to address this common deficiency in teaching materials. The case study facilitates students' accurate understanding and proper differentiation of these test applications while strengthening their scientific decision-making skills. This teaching resource can be effectively incorporated into classroom instruction, supplementary materials, or laboratory preparation to support subsequent specialized study and research training.

Key words: Paired t-test, Two-sample t-test, Significant test, Grouped data analysis