Which of the following best describes normal distribution?

Normal distribution is best described as a symmetrical bell-shaped graph representing variable distribution. This type of distribution is characterized by its characteristic bell shape, where the highest point occurs at the mean, median, and mode of the data set, and the probabilities for values taper off equally in both directions away from the center.

Key features of normal distribution include that approximately 68% of the data falls within one standard deviation from the mean, about 95% falls within two standard deviations, and about 99.7% within three standard deviations. This property makes the normal distribution fundamental in statistics, as many statistical tests assume normality in the data.

In contrast, a skewed graph would not have the symmetrical bell shape, indicating an uneven distribution of data points. An irregular distribution does not follow the characteristics of normal distribution and may not conform to any particular shape. Similarly, a collection of outliers indicates data points that are significantly different from the rest, which disrupts the normal characteristics of distribution, leading to a model that does not represent the data accurately.