Normal curve
The normal curve, also known as the Gaussian distribution or bell curve, is a probability distribution that represents a symmetrical pattern of data
The normal curve, also known as the Gaussian distribution or bell curve, is a probability distribution that represents a symmetrical pattern of data. It is characterized by a smooth, symmetrical bell-shaped curve, with the highest point at the mean (average) of the data.
The normal curve is defined by two parameters: the mean (μ) and the standard deviation (σ). The mean represents the central tendency of the data, while the standard deviation measures the spread or variability around the mean.
In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean (34% on each side), 95% falls within two standard deviations (47.5% on each side), and 99.7% falls within three standard deviations (almost 50% on each side and 0.3% in the tails).
The normal curve is widely used in statistics and probability theory. Many real-world phenomena can be approximated by a normal distribution, such as heights and weights of a population, test scores, and measurement errors. It provides a useful framework for understanding and analyzing data, making predictions, and performing statistical inference.
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