**Core Concept**
Negatively skewed data is a type of distribution where the majority of the data points are concentrated on the right side of the distribution, with fewer data points on the left side. This type of distribution is often seen in real-world data, especially when there is a floor effect or a minimum value that cannot be achieved.

**Why the Correct Answer is Right**
Negatively skewed data is characterized by a longer tail on the left side, indicating that there are fewer extreme values on the left. This type of distribution is often seen in data that has a floor effect, such as exam scores where the minimum score is 0. The mean is typically less than the median in negatively skewed data, and the mode is often the most frequent value. In this type of distribution, the skewness is negative, indicating that the data is more spread out on the left side.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because negatively skewed data is characterized by a longer tail on the left side, not the right side. A longer tail on the right side would indicate positively skewed data.
**Option B:** This option is incorrect because the mode is the most frequent value in the data, but it is not necessarily the median or the mean. In negatively skewed data, the mode is often the most frequent value, but it may not be the same as the median or the mean.
**Option C:** This option is incorrect because the mean is typically less than the median in negatively skewed data, but it is not always the case. The relationship between the mean and the median can vary depending on the specific data distribution.

**Clinical Pearl / High-Yield Fact**
When analyzing data, it's essential to consider the type of distribution and the potential floor or ceiling effects that may be present. Negatively skewed data can be challenging to analyze, and it's crucial to use the right statistical methods and techniques to understand the underlying patterns and trends.

**Correct Answer:** C.