The normal distribution, also known as the Gaussian distribution, is a symmetric probability distribution centred on the mean, indicating that data around the mean occur more frequently than data far from it. The normal distribution will show as a bell curve on a graph.
The mean, median, and mode are all equal in normal distributions, which are symmetric, unimodal, and asymptotic. Around its centre, a normal distribution is exactly symmetrical.
The mean of a standard normal distribution is 0 and the standard deviation is 1. The z distribution is another name for this. The symbol N ( μ , σ ) denotes a normal distribution, with N being the mean of the distribution and S denoting the standard deviation of the distribution.
The numbers are evenly distributed both above and below the mean in a normal distribution. If the mean, mode, and median are all equal, the population has a perfectly normal distribution. The mean, mode, and median for a population of 3,4,5,5,5,6,7 are all 5.
Because the probability density graph of the normal distribution resembles a bell, it is commonly referred to as the bell curve. The Gaussian distribution is named after the German mathematician Carl Gauss, who first characterised it.
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Sunita Singhal
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please provide notes also in pdf
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Montu Mali
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nice ☺️👍
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Abdul Samed
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please provide course notes
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Shashi Kumar
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great resource to learn data science in hindi. but in this particular video lecture there is a mistake....actually mutually exclusive event can never be independent event.
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Nikhil Fapale
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it really amazing to study....and easily understand difficult concepts...i hope you make more video on like power bi and nueral network model....its really helpful....thank you for these
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