What characteristic describes a leptokurtic distribution?

A leptokurtic distribution is characterized by a distribution curve that is tall, thin, and peaked, which reflects a higher concentration of data points around the mean compared to a normal distribution. This peakedness is an indicator of the kurtosis of the distribution being greater than 3, which signifies a higher likelihood of producing extreme values (outliers) when compared to a normal distribution.

In contrast to other types of distributions, the leptokurtic shape indicates that there are fewer observations in the tails of the distribution and a sharp peak at the center. This property is essential in statistical analysis, especially when assessing risk or variability in data.

It's also important to recognize how this characteristic differs from the other options provided. A distribution curve that is flat and wide refers to a platykurtic distribution, which has lower kurtosis. The option regarding kurtosis being equal to 3 describes a mesokurtic distribution, which is typical of the normal distribution. Lastly, while symmetry can be a property of various distributions, a leptokurtic distribution is not necessarily symmetrical, as its main trait is the peakedness rather than the shape's symmetry.