Which of the following best describes a normal distribution?

A normal distribution is best described as a symmetrical bell-shaped curve where most values cluster around the mean. This characteristic signifies that the majority of the observations are concentrated near the central value, tapering off equally towards the extremes. The symmetry indicates that there is an equal probability of values falling above or below the mean, making it a crucial concept in statistics as it represents a pattern of variability common in many natural phenomena.

In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, about 95% falls within two standard deviations, and around 99.7% falls within three standard deviations. This predictable pattern is foundational for inferential statistics, allowing for the application of various statistical techniques that assume normality.

The other options describe distributions that do not align with the characteristics of a normal distribution. A distribution with multiple peaks suggests multimodality, which is fundamentally different from the single-peak structure of a normal distribution. Unique data points indicate a lack of repetition, diverging from the clusters expected in a normal distribution. Lastly, a jagged distribution would imply erratic variability not present in the smooth, continuous curve of a normal distribution. Each of these alternatives points to distributions that have distinct shapes and characteristics that set