What term describes a distribution where scores are piled up at one end?

What term describes a distribution where scores are piled up at one end?

• A. Normal distribution
• B. Uniform distribution
• C. Skewed distribution
• D. Binomial distribution

Answer: (C)

A skewed distribution refers to a data set where scores are not evenly distributed and are "piled up" more on one side of the scale than the other. This phenomenon often indicates that there are outliers or extreme values affecting the average and overall shape of the distribution. In a skewed distribution, you will typically see a longer tail on one side—either to the left (negatively skewed) or to the right (positively skewed). This characteristic is important for understanding various statistical measures and how they may be influenced by the distribution of data points. In contrast, a normal distribution depicts data that is symmetrically distributed around a central mean, forming a bell-shaped curve, while a uniform distribution has all outcomes equally likely, creating a flat distribution. A binomial distribution represents the number of successes in a fixed number of independent yes/no trials, which does not align with the concept of scores piling up at one end. Thus, the term "skewed distribution" is the most accurate descriptor for the scenario outlined in the question.

A skewed distribution refers to a data set where scores are not evenly distributed and are "piled up" more on one side of the scale than the other. This phenomenon often indicates that there are outliers or extreme values affecting the average and overall shape of the distribution. In a skewed distribution, you will typically see a longer tail on one side—either to the left (negatively skewed) or to the right (positively skewed). This characteristic is important for understanding various statistical measures and how they may be influenced by the distribution of data points.

In contrast, a normal distribution depicts data that is symmetrically distributed around a central mean, forming a bell-shaped curve, while a uniform distribution has all outcomes equally likely, creating a flat distribution. A binomial distribution represents the number of successes in a fixed number of independent yes/no trials, which does not align with the concept of scores piling up at one end. Thus, the term "skewed distribution" is the most accurate descriptor for the scenario outlined in the question.