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Random Numbers from Normal Distribution with Specific Meanand Variance

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This example shows how to create an array ofrandom floating-point numbers that are drawn from a normal distributionhaving a mean of 500 and variance of 25.

The randn function returns a sample ofrandom numbers from a normal distribution with mean 0 and variance1. The general theory of random variables states that if x isa random variable whose mean is $${\mu }_x$$ andvariance is $${\sigma }_x^2$$,then the random variable, y, defined by $$y=ax+b,$$where a and b areconstants, has mean $${\mu }_y=a{\mu }_x+b$$ andvariance $${\sigma }_y^2=a^2{\sigma }_x^2.$$ Youcan apply this concept to get a sample of normally distributed randomnumbers with mean 500 and variance 25.

First, initialize the random number generator to make the results in this example repeatable.

Create a vector of 1000 random values drawn from a normal distribution with a mean of 500 and a standard deviation of 5.

Calculate the sample mean, standard deviation, and variance.

The mean and variance are not 500 and 25 exactly because they are calculated from a sampling of the distribution.

See Also

randn | rng

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