Which type of data typically does NOT lead to a normal distribution?

Skewed data typically does not lead to a normal distribution due to its asymmetrical nature. In a normal distribution, the values are symmetrically distributed around the mean, following a bell-shaped curve. Skewed data, on the other hand, contains a tail on one side, resulting in a distribution that is not balanced. This skewing can occur in either direction, leading to a concentration of values on one end of the distribution while the other end tapers off, making it incompatible with the characteristics of normal distribution.

Continuous data, symmetric data, and quantitative data can all exhibit normal distribution under the right conditions. Continuous data can take on any value within a range and may fit a normal distribution. Symmetric data, by definition, is balanced around a central point and can produce a normal distribution. Quantitative data refers to numerical data that can be measured and is also capable of forming a normal distribution, especially when collected from large enough samples.