What type of distribution is characterized by scores that lack symmetry around the average?

A skewed distribution is characterized by scores that lack symmetry around the average, meaning it has a tail that extends more to one side than the other. This results in the mean, median, and mode being located at different points on the number line. In a skewed distribution, you can have either a positive skew, where the tail on the right side (higher scores) is longer or a negative skew, where the tail on the left side (lower scores) is longer. This lack of symmetry is a fundamental aspect that differentiates a skewed distribution from other types mentioned in the choices.

For context, a normal distribution, characterized by its bell-shaped curve, is perfectly symmetrical with the mean, median, and mode all being equal and located at the center. A bimodal distribution has two different modes, or peaks, and may or may not be symmetric. A uniform distribution has all outcomes occurring with the same frequency, making it flat rather than skewed. Each of these distributions illustrates different characteristics of data that help researchers understand patterns and behaviors in datasets.