What characteristic of normal distribution is often depicted by a histogram?

A characteristic of normal distribution that is often depicted by a histogram is the bell-shaped curve. This shape is fundamental to the concept of normal distribution, which is symmetrical and displays that most data points cluster around a central peak, tapering off equally in both directions towards the tails. When a dataset is graphed in a histogram format, the frequencies of the data points will typically show this bell shape, indicating that the majority of values are around the mean, with fewer occurrences as you move away from the center.

In normal distribution, approximately 68% of the data falls within one standard deviation from the mean, around 95% within two standard deviations, and about 99.7% within three standard deviations. These percentages contribute to the bell shape, emphasizing the clustering of data points around the mean.

Other forms of distributions, such as skewed distribution, bimodal distribution, or an exponential curve, do not represent the normal distribution's defining characteristics. A skewed distribution would show an asymmetrical shape, a bimodal distribution would have two distinct peaks, and an exponential curve suggests a very different growth pattern, often related to rate processes rather than a distribution of values around a mean. Thus, the bell-shaped curve effectively encapsulates the essence of a