A good friend of mine has been learning how to use R for his research in community ecology for the last year. He reminded me today of an exercise I wrote up for him awhile back to introduce the use of *for* loops. The exercise is a demonstration of the sampling distribution and goes as such:

The sampling distribution describes the distribution of sample means. In this exercise a simple experiment is performed where a population is sampled, and the mean of that sample is recorded. This is to be repeated several times in a *for* loop, with each sample mean recorded so we may later examine their distribution.

- Create a population of size 10000, with some normally distributed trait (mean = 10, standard deviation = 10)
- Create a
*for*loop that repeats 1000 times. Take a sample of size 100 from this population at every iteration, and save each sample mean. - Create a histogram of your 1000 recorded sample means.
- Find the mean and standard deviation of your recorded sample means. Compare these to the mean and standard deviation of the original population.

Needed R functions: *rnorm(), numeric(), for(){}, sample(), mean(), sd(), hist()*