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A normal distribution is characterized by the fact that the mean, median, and mode are all equal. This equality indicates a symmetrical distribution where the data is evenly distributed around the central point. In a normal distribution, the bell-shaped curve represents this symmetry, meaning that half of the observations lie to the left of the mean and half lie to the right.

The equal relationship among the mean, median, and mode is a defining feature of the normal curve. This balance is what allows for the properties associated with normal distributions, such as 68-95-99.7 rule, which describes how data points are spread around the mean in one, two, and three standard deviations.

Other options do not accurately reflect the characteristics of a normal distribution. The mean being greater than the median would indicate a right-skewed distribution, while being skewed to one side also signifies a lack of symmetry. The presence or absence of outliers can vary more broadly in different data sets but does not define a normal distribution specifically.