Data Analytics Course: What is Normal Distribution? | Intellipaat

  Normal distribution, also known as Gaussian distribution or bell curve, is a statistical concept that describes a symmetric, bell-shaped probability distribution. In a normal distribution, the values are concentrated around the mean (average), and the distribution of data is characterized by its predictable shape.   Key characteristics of a normal distribution include:   Symmetry: The normal distribution is symmetric, meaning that the left and right sides of the distribution are mirror images of each other. The center point, or peak, of the curve represents the mean.   Bell-Shaped Curve: The distribution forms a bell-shaped curve, with the highest point at the mean and gradually tapering off as values move away from the mean.   Mean, Median, and Mode: In a normal distribution, the mean, median, and mode are all located at the center of the distribution, making them equal. This is true for a perfectly normal distribution.   Standard Deviation: The spread or dispersion of data in a normal distribution is quantified by the standard deviation. About 68% of the data falls within one standard deviation from the mean, 95% within two standard deviations, and 99.7% within three standard deviations.   Empirical Rule (68-95-99.7 Rule): This rule states that in a normal distribution:   Approximately 68% of the data falls within one standard deviation from the mean. Approximately 95% falls within two standard deviations. Approximately 99.7% falls within three standard deviations.