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empirical probability
P(e)= frequency of E/ # of trials of experiment
Classical probability
P(E)= #of ways E can occur/ # of possible outcomes= N(E)/N(S)
Addition rule for disjoint events
P(E or F)= P(E)+P(F)
General Addition Rule
P(A or B) = P(A) + P(B) - P(A and B)
Complement Rule
P(A^c) = 1 - P(A)
Multiplication rule for independent events
P(A and B) = P(A)*P(B)
Conditional probability rule
P(A|B) = P(A and B) / P(B)
General Multiplication Rule
P(A and B) = P(A) * P(B|A)
Permutation Formula
nPr = n!/(n-r)!
Combination Formula
nCr = n!/r!(n-r)!
Mean of a Discrete Random Variable
µx=∑(x*P(x))
Standard deviation of a discrete random variable
σx=√∑(xi-μx)²*(px))
Binomial Probability Formula
P(x)= (nCx) (p^x) (q^n-x)
mean of a binomial distribution
μx = n * P
standard deviation of a binomial distribution
σ = √np(1-p)
What does the random variable represent for the binomial distribution?
Number of Successes out of "n" trials.