What is a dataset's shape indicating a normal distribution commonly referred to as?

A dataset's shape indicating a normal distribution is commonly referred to as bell-shaped. This term reflects the characteristic appearance of a normal distribution graph, which resembles the shape of a bell. In a normal distribution, the data is symmetrically distributed around the mean, with most of the observations clustering around the center and tapering off equally on both sides toward the extremes.

This bell-shaped curve highlights key statistical properties, such as the mean, median, and mode all being located at the center, reinforcing the idea of symmetry and the consistent behavior of data in a normal distribution. Understanding this shape is crucial for many statistical analyses and inferential statistics, as it underlies various parametric tests that assume data normality for valid results. The bell shape is essential for recognizing how data behaves and helps in calculating probabilities, making it a foundational concept in statistics.