Computer Lab supervisions - Probability

Probability Theory is a beautiful subject. It might seem a bit obscure at first to some and if that's the case, don't despair and don't give up. You can also fire a few emails to me if you just can't get your head around it. Once you understand that, ultimately, probability is just a mathematical measure of uncertainty and once you start concentrating on understanding the phenomena rather than blindly applying formulas, you are on the path of becoming a successful thinking probabilist.

We may do only three supervisions, depending on progress and request.

Supervision 1:

Supervision 2:

  • Problems 10-15 from Richard Gibbens' Problem Sheet.
  • Show that for any discrete random variable that has a PGF, its probability mass function p(k) is given by p(k) = G(k)(0) / k!, where G(k)(z) is the kth derivative of the PGF function G(z).
  • Questions 1-3 from my Question list.

Supervision 3:

  • Given a random variable X, either discrete or continuous, we define M(t) = E[etX], assuming this expectation exists. Show that the nth moment of X, i.e. E[Xn], in both discrete and continuous cases is given by E[Xn] = M(n)(0), where M(n)(t) is the nth derivative of M(t). For a discrete X, assume a probability mass function p(k). For a continuous X, assume a continuous probability density function f(x).
  • Problems 5-9, 12, 13, 17, 19, 22 from my Question list.

Supervision 4:

  • Questions 4, 10, 14, 16, 18, 21 from my Question list.
    NOTE: These are non-trivial, don't start the work late.