What term describes a distribution that follows the shape of a normal curve?

The term that describes a distribution that follows the shape of a normal curve is referred to as a Gaussian curve. This term is derived from Carl Friedrich Gauss, who contributed significantly to the understanding of this distribution. A Gaussian curve is characterized by its symmetrical, bell-shaped outline, which indicates that the data points are more concentrated around the mean, with frequencies tapering off as you move away from the center. This shape reflects the properties of many natural and statistical phenomena, where the majority of occurrences are near the average and fewer occur as you move away in either direction.

In comparison, the other options represent different types of distributions. The exponential curve typically applies to data that follows a decreasing rate of occurrence, such as in decay processes. A bimodal curve has two distinct peaks, indicating that the data set has two different modes or most common values, while a uniform curve suggests a constant probability across all outcomes, devoid of peaks or valleys. Understanding these differences helps in identifying the correct applications of each distribution type in data science and statistics.