**Core Concept**
The Kaplan-Meier survival curve is a graphical representation of the probability of survival over time in a group of patients. It is commonly used in clinical research to compare the survival rates of different treatment groups or to analyze the effect of a particular variable on survival. The key concept being tested here is the statistical method used to compare these survival curves between groups.

**Why the Correct Answer is Right**
The log rank test is a statistical method used to compare the Kaplan-Meier survival curves between two or more groups. It works by calculating the difference in the number of events (e.g., deaths) between the groups at each time point, and then testing whether this difference is statistically significant. The log rank test is a non-parametric test, meaning it does not assume a specific distribution of the data, making it a good choice for comparing survival curves. The log rank test is specifically designed to handle censored data, where not all patients have reached the event of interest (e.g., death) by the end of the study.

**Why Each Wrong Option is Incorrect**
**Option A:** The t-test is a parametric test used to compare the means of two groups, which is not applicable to comparing survival curves.
**Option B:** The Chi-square test is a non-parametric test used to compare categorical data, not survival times.
**Option D:** Whitney's test, also known as the Mann-Whitney U test, is a non-parametric test used to compare the distributions of two groups, but it is not specifically designed for comparing survival curves.

**Clinical Pearl / High-Yield Fact**
When comparing survival curves, always check for censoring and consider using a non-parametric test like the log rank test, as parametric tests may not be robust to censored data.

**✓ Correct Answer: C. Log rank test**