This assignment analyzes the Wage dataset using various statistical techniques to perform hypothesis testing. The student assesses the normality of the wage variable, finding it non-normal and suggesting a transformation. The assignment then uses an independent t-test to compare wages between the information and industrial sectors, rejecting the null hypothesis and concluding a significant wage difference. A one-way ANOVA is employed to determine wage differences across races, leading to the rejection of the null hypothesis and a post-hoc Tukey HSD test identifies specific racial wage disparities. The student also explores non-parametric methods like the Kruskal-Wallis test and Dunn's post-hoc test for comparison. Finally, the student conducts another hypothesis test, using a one-way ANOVA to analyze wage differences based on education levels, rejecting the null hypothesis and using a post-hoc Tukey HSD to determine which education levels have significant wage differences. The assignment includes R code and references.