Define normal distribution. Discuss the two parameters which are integral to its definition.

Normal Distribution:

The normal distribution, also known as the Gaussian distribution, is a fundamental concept in statistics and probability theory. It is a continuous probability distribution that is symmetric and bell-shaped. The normal distribution is characterized by its probability density function (PDF), which is often represented by the bell-shaped curve.

Parameters of the Normal Distribution:

The normal distribution is defined by two parameters: the mean (μ) and the standard deviation (σ). These parameters play a crucial role in shaping the distribution and determining its properties.

1. Mean (μ): The mean, denoted as μ, represents the central or average value of the distribution. In the context of the normal distribution, the mean is also the location of the peak of the bell-shaped curve. It serves as a measure _______ ____ _________ _____ _______ ___ __________ ________.
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