Final answer:
The normal distribution is a continuous probability distribution curve that is widely used in various disciplines. It is characterized by a bell-shaped graph and has a mean and standard deviation.
Step-by-step explanation:
The statement is true. The normal distribution, often represented as a bell-shaped curve, is a classic example of a continuous probability distribution. In a continuous probability distribution, the random variable can take any value within a specified range. The normal distribution is characterized by its symmetric bell-shaped curve, where the majority of the data falls around the mean, and the probability density gradually decreases as values move away from the mean in either direction. The continuous nature of the normal distribution means that, theoretically, a data point can have an infinite number of possible values within the range. This distinguishes it from discrete probability distributions, where the random variable can only take distinct, separate values. The normal distribution is widely applicable in statistics and probability theory, particularly in cases where the distribution of data is unknown or complex.