ABSTRACT
This chapter focuses on statistical techniques for comparing the means of different groups, specifically independent-samples t-tests and one-way ANOVA. It outlines when each test is appropriate: t-tests for comparing two groups and ANOVA for comparing more than two. The chapter details the assumptions underlying these tests, such as normality and homogeneity of variances, and explains the importance of verifying them to ensure valid results. Procedures for conducting t-tests (including interpretation of t-statistic and p-value) and ANOVA (with F-statistic and understanding between-group vs. within-group variation) are described. The concept of statistical significance in group differences is illustrated with practical examples. The chapter also introduces post-hoc analyses following ANOVA to pinpoint which specific group differences are significant. Emphasis is placed on practical applications (e.g., experimental vs. control group comparisons) and common pitfalls (like misuse of multiple t-tests instead of ANOVA). Readers learn not only how to perform these tests but also how to report and interpret findings responsibly.
