1. **Problem Statement:** We want to test if the distributions of access to basic water services in rural and urban areas are the same. 2. **Null Hypothesis ($H_0$):** The distributions of access to basic water services in rural and urban areas are the same. 3. **Understanding the Data:** The histogram shows two samples: rural (wat_bas_r) and urban (wat_bas_u) access frequencies across percentage bins. 4. **Choosing the Test:** - The Kolmogorov-Smirnov test compares the entire distributions of two independent samples and is non-parametric. - The independent two-sample z-test compares means assuming normality and large samples. - The paired two-sample z-test is for paired data (same subjects measured twice). 5. **Why Kolmogorov-Smirnov Test is Appropriate:** - We want to compare distributions, not just means. - Samples are independent (rural vs urban). - The histogram suggests different shapes and frequencies, so a distribution test is better. 6. **Conclusion:** The most appropriate test is the Kolmogorov-Smirnov test. **Final answer:** Kolmogorov-Smirnov test