**Core Concept**
Positively skewed distribution refers to a type of data dispersion where the majority of the data points are concentrated on the left side of the distribution, with a long tail extending towards the right. This type of skewness often occurs in medical data, such as patient weight or blood pressure, where most individuals have a normal or lower-than-average value, but a small percentage have significantly higher values.

**Why the Correct Answer is Right**
In a positively skewed distribution, the mean value is typically greater than the median value. This is because the long tail of the distribution pulls the mean value towards the higher end of the data. In medical research, this type of skewness can be problematic, as it may lead to biased estimates of the population mean. To address this issue, researchers often use non-parametric tests or transform the data using techniques such as logarithmic transformation.

**Why Each Wrong Option is Incorrect**
**Option A:** Incorrect because it does not describe the characteristics of a positively skewed distribution.
**Option B:** Incorrect because it is a description of a negatively skewed distribution, where the majority of data points are concentrated on the right side of the distribution.
**Option C:** Incorrect because it is a description of a normal distribution, which is symmetric and does not exhibit skewness.
**Option D:** Incorrect because it is a description of a bimodal distribution, which has two distinct peaks and does not exhibit skewness.

**Clinical Pearl / High-Yield Fact**
When analyzing medical data, it is essential to check for skewness and consider using non-parametric tests or data transformation techniques to ensure accurate estimates of the population mean.

**Correct Answer: B. A distribution in which the majority of the data points are concentrated on the right side.**