**Core Concept**
The question is testing the understanding of statistical methods used for comparing two groups with variable differences. In medical research, it's essential to choose the right statistical test to compare groups, especially when the data doesn't meet the assumptions of a particular test.

**Why the Correct Answer is Right**
The correct answer is the **Wilcoxon Rank-Sum Test**, also known as the Mann-Whitney U test. This non-parametric test is used to compare two independent groups when the data is not normally distributed or when the sample size is small. The test ranks the data from both groups combined and then calculates the sum of ranks for each group. This allows for the comparison of the two groups without assuming a normal distribution.

**Why Each Wrong Option is Incorrect**
**Option A:** **t-test** is incorrect because it assumes normal distribution of the data, which may not be the case in this scenario.

**Option B:** **ANOVA** is incorrect because it's used to compare more than two groups, whereas the question asks for a comparison of two groups.

**Option C:** **Chi-Square Test** is incorrect because it's used for categorical data, whereas the question implies that the data is continuous.

**Clinical Pearl / High-Yield Fact**
Remember that non-parametric tests like the Wilcoxon Rank-Sum Test are essential when dealing with non-normal or ordinal data, and they provide a valuable alternative to parametric tests like the t-test.

**Correct Answer: . Wilcoxon Rank-Sum Test**