What is a characteristic of Normal Distribution?

Normal distribution is a statistical concept where the data tends to cluster around a central value, typically represented by the mean. In a normal distribution, most of the observations fall within a specific range around the mean, and as you move away from the mean, the frequency of observations decreases symmetrically. This characteristic results in the familiar bell-shaped curve often associated with the normal distribution.

The importance of the mean in normal distribution is emphasized since approximately 68% of the data points fall within one standard deviation of the mean, about 95% within two standard deviations, and about 99.7% within three standard deviations. This property is fundamental in many statistical analyses, as it helps in making inferences about the population from which the sample is drawn.

In contrast, other options such as skewed data indicate a lack of symmetry, which is not a feature of a normal distribution. Uniformly distributed data suggests that all outcomes are equally likely, which does not capture the clustering around a mean characteristic of normal distribution. Data with multiple peaks is indicative of a multimodal distribution, not a normal distribution, which has a single peak. Understanding these characteristics is vital in fields such as quality control, finance, and research, where normal distribution assumptions can significantly influence decision