1. Use the rnorm() function to generate a random sample of size N = 50 from the normal distribution N(µ, o²), with u = 23 and o = 3. Record this sample as a vector v. %3D (i) Compute the sample mean...

Extracted text: 1. Use the rnorm() function to generate a random sample of size N = 50 from the normal distribution N(µ, o²), with u = 23 and o = 3. Record this sample as a vector v. %3D (i) Compute the sample mean of of v. (ii) Run a bootstrap procedure, with limit B= 5000, to generate re-samples i = 1, 2, 3, ,B. Compute the sample mean replicants u. (i) (2) (iii) Plot a histogram for the sample mean replicants u, i = 1,2. B. (iv) Compute the bootstrap bias bias(uv) and the bootstrap standard error SE(). (v) Theoretical arguments predict that the standard deviation of uy is given by 0/VN. Compare this value with the bootstrap standard error computed at (iv).