R Exercises | Programming Exercises for Finance in the R Language

Probability and Statistics: Exercises

5. Sampling uncertainty. The function rnorm(n,mean,sd) generates n draws from a normal distribution. Draw 10 and then 1000 observations from a normal distribution with mean 5 and standard deviation 20. Compute the mean in each case.



                            # Draw 10 observations from a normal distribution.
                            draws_10 <- ___(10, ___, ___)

                            # Draw 1000 observations from a normal distribution.
                            draws_1000 <- ___

                            # Print mean of draws_10.
                            print(___(draws_10))

                            # Print mean of draws_1000.
                            ___



                            # Draw 10 observations from a normal distribution.
                            draws_10 <- rnorm(10, 5, 20)

                            # Draw 1000 observations from a normal distribution.
                            draws_1000 <- rnorm(1000, 5, 20)

                            # Print mean of draws_10.
                            print(mean(draws_10))

                            # Print mean of draws_1000.
                            print(mean(draws_1000))


                            test_error()
                            test_object("draws_10", incorrect_msg="Did you enter the correct arguments to `rnorm()`?")
                            test_object("draws_1000", incorrect_msg="Did you enter the correct arguments to `rnorm()`?")
                            test_function("mean", incorrect_msg="Did you use the function `mean()`?")
                            success_msg("Well done! What happens to the mean as you increase the number of observations?")

Did you use the rnorm() function?

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