**Core Concept**
A frequency distribution is a representation of the number of observations that fall into each category or group in a dataset. In statistics, the shape of a frequency distribution can be described as symmetrical or asymmetrical. A symmetrical distribution has similar shapes on both sides of the central tendency, whereas an asymmetrical distribution does not have this characteristic. Non-symmetrical frequency distributions can be further classified into positively skewed and negatively skewed distributions.

**Why the Correct Answer is Right**
A non-symmetrical frequency distribution is characterized by a lack of symmetry around the central tendency. This can be due to the presence of outliers or extreme values in the dataset. In a positively skewed distribution, the tail on the right side is longer than the tail on the left side, indicating that there are more extreme values on the higher end of the distribution. Conversely, in a negatively skewed distribution, the tail on the left side is longer than the tail on the right side, indicating that there are more extreme values on the lower end of the distribution.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is not relevant to the concept of frequency distribution shape.
**Option B:** This option may be a distractor, but it does not accurately describe a non-symmetrical frequency distribution.
**Option D:** This option is not a valid description of a frequency distribution shape.

**Clinical Pearl / High-Yield Fact**
When analyzing a dataset, it's essential to consider the shape of the frequency distribution to understand the underlying data characteristics. Non-symmetrical distributions can often indicate the presence of outliers or extreme values, which can affect statistical analysis and interpretation.

**Correct Answer: C. Skewed distribution.**