`
`Random Numbers from Normal Distribution with Specific Mean and Variance - MATLAB & Simulink
`
`Random Numbers from Normal Distribution with Specific Mean
`and Variance
`
`This example shows how to create an array of random floating-point numbers that are drawn from a normal distribution
`having a mean of 500 and variance of 25.
`
`
`σ2
`
`y= a2σ2x.
`
`y= ax+ b,
`
`The randn function returns a sample of random numbers from a normal distribution with mean 0 and variance 1. The
`μx
`general theory of random variables states that if x is a random variable whose mean is
` and variance is
`, then the
`x
`random variable, y, defined by
`where a and b are constants, has mean
` and variance
` You can apply this concept to get a sample of normally distributed random numbers with mean 500 and
`variance 25.
`
`μy= aμx+ b
`
`σ2
`
`First, initialize the random number generator to make the results in this example repeatable.
`
`rng(0,'twister');
`
`Create a vector of 1000 random values drawn from a normal distribution with a mean of 500 and a standard deviation of 5.
`
`a = 5;
`b = 500;
`y = a.*randn(1000,1) + b;
`
`Calculate the sample mean, standard deviation, and variance.
`
`stats = [mean(y) std(y) var(y)]
`
`stats =
`
` 499.8368 4.9948 24.9483
`
`The mean and variance are not 500 and 25 exactly because they are calculated from a sampling of the distribution.
`
`http://www.mathworks.com/help/matlab/math/random-numbers-with-specific-mean-and-variance.html
`
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`
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