Final answer:
In the context of this question, C) Skewed Distribution is the correct option as it describes a distribution where scores are piled up at one end.
Step-by-step explanation:
If scores pile up at one end of the distribution or the other, it is said to be a skewed distribution. This is because in such a distribution, there is a longer tail on one side of the peak than on the other. If the tail is on the right, it is called right-skewed or positively skewed. If it is on the left, it is called left-skewed or negatively skewed. Skewness refers to the extent to which the scores of the distribution are not symmetrical about its mean. A symmetrical, or normal, distribution will have the mean and median at the same point, which would be at the mode in a perfectly symmetrical (unimodal) distribution.
When a histogram shows that data values are piled up at one end and the tail extends to the other, this indicates skewness. The mean will be pulled toward the longer tail, and the median will be closer to the peak of the distribution. Thus, in a left-skewed distribution, the mean is less than the median, because the tail extends to the left. In a right-skewed distribution, the mean is greater than the median, since the tail extends to the right. It is important to understand skewness when discussing probability distributions and other statistical analyses.
In the context of this question, C) Skewed Distribution is the correct option as it describes a distribution where scores are piled up at one end.