lecture_35

Final 1:00 - 3:00

• No decks of cards
• No Baye's
• Little or nothing on zeng letures
• about 20% more content than the midterm

Review

• Expectation
• Variance
• Joint Distribution and Densities
• Covariance
• Sums of random variables
• Sums of independent random variables
• Use of moment generating functions
• The page 358-359 tables:
  • know about various distrobutions and their moment generating functions
  • ESPECIALLY
    • Binomial
    • Poisson
    • Geometric
    • Uniform
    • Exponential
    • Normal

DNHI

Say [M(t) = \frac{ 1}{ n + 1} (1 + e^t + e^{2t} + \cdots + e^{n t})]

• find [E(X)]
  • [M'(0) = \frac{ 1}{ n + 1}( 1 + 2 + \cdots + n) = \frac{ n}{ 2}]
• find [Var( X)]
  • [M''( 0) - (M'(0))^2 = \frac{ n(2n + 1)}{ 6} - \frac{ n^2}{ 4}]