Questions Flashcards
(35 cards)
Probability
0<=P(event)<=1
Objective Approach
no. occurences/ total trials or outcomes
Adding Mutually Exclusive Events
P(A) + P(B)
Adding Not Mutually Exclusive Events
P(A) + P(B) - P(A and B)
Statistically Independent : Joint
P(A) x P(B)
Statistically dependent : Joint
P(A\B) x P(B)
Statistically Independent : Conditional
P(A\B) = P(A)
Statistically dependent : Conditional
P(A\B) = P(AB) / P(B)
Normal distrib approx. probabilities
68(.268) /95(.45)/ 99.7(3)
Bayes Theorem
(P(B\A)P(A) / (P(B\A)P(A) + P(B/A’)P(A’)
Mean/ Expected Value
E xiP(xi)
Standard Variance
(E(ci-mu)^2)/n-1
Variance
E [Xi-E(x)^2} P(x)
Binomial Distribution (BD): Successes
(n!)/(r!(n-r)!) *P^r q^(n-r)
BD: expected value /mean
np
BD: Variance
npq
Normal distrib f(x)
check paper
z score
(x-mu)/standard deviation
Coercion of realism
WA=COR(Max. Row) + (1-CoR)(Min.Row) ===Highest Value
Equally Likely
(Max+Min)/no.
Minimax Regret
Best Payoff-Each payoff ===Minimum Value
Expected Monetary Value
(payoff 1t state)(Psecond)+(Payoff 2nd)(Psecon)+…n
Expected Value of Perfect Information
EVwPI-Max. Emv
EVwPI
(Max each times probs)