# Binomial distribution sample vs. population mean

I'm a little confused at this question posed by my prof. He asked us to generate a binomial distribution in R and input whatever variables we wanted.

x = rbinom(50, 10, 0.83)


Then he asks us to compute the sample mean, sample variance, population mean and population variance of the distribution.

sample mean:  mean(x)
sample var:   var(x)


But I have no idea what he intends we do to get the population mean and variance. Don't you need a larger set of data to be the population and a smaller set to be the sample? I only (seem to) have one set here.

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In your example, the population mean is $10\cdot0.83 = 8.3$ and the population variance is $10\cdot0.83\cdot(1-0.83)=1.411$.