The function `rnorm()`

generates automatically a series of random values which are normally distributed. This comes quite handy when you want to test functions, statistical analyses or scripts on a random dataset, and you need to be sure that the content is normally distributed beforehand.

`rnorm()`

needs the following information:

- n, the number of values needed,
- mean, the mean of the values to be generated,
- sd, the standard deviation of the data set

The syntax is as follows:

[code language=”r”]

rnorm(n, mean, sd)

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Here is an example where we want to generate a series (called random.set) of 200 values, which mean is 42 and which standard deviation is 8:

[code language=”r”]

random.set <- rnorm(200, 42, 8)

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And the first values in the data set look like this:

This is what you get if you plot the data set with `hist()`

[code language=”r”]

hist(random.set)

[/code]

A density plot with `plot(density())`

can also be useful to visualize the distribution:

[code language=”r”]

plot(density(random.set))

[/code]