All possible outcomes of an experiment or set of trials
Sample Space
P(A u B) = P(A) + P(B) - P(A n B)
General Addition Rule
P(B) = P(B|A)
Proving Independence
μx =E(X)
Discrete Random Variable Means
When reporting mean and SD in dollars, values must...
be converted to $ BEFORE input and output from transformation equations
A specific desired outcome or set of outcomes of an experiment or set of trials
Event
P(A u B) = P(A) + P(B)
Mutually Excllusive Addition Rule
P(A|B) = P(A n B) / P(B)
Conditional Probability
μx = np
Binomial Distribution Means
Expected value of the addition/subtraction of two variables
E(X+/-Y) = E(X) +/- E(Y)
Two events that can not happen together
Mutually Exclusive
P(AC) = 1 - P(A)
Complement Rule
P(A n Bc) = P(A) - P(A n B)
Complement Intersection equation
μx = 1/p
Geometric Distribution Means
Standard deviation of the addition/subtraction of two variables
σX+/-Y = √σX2 + σY2
Two events that do not influence one another
Independent
P(A n B) + P(A) * P(B)
Independent Multiplication Rule
P(X=x) = (n over x) px(1-p)n-x
Binomial Notation
σx = (√1-p) / p
Geometric Standard Deviations
Mean transformation: E(A+Bx)
E(A+Bx) = A + (B * (E(X))
2 possible outcomes, fixed probability, independent, fixed # trials
Bernoulli Trial
P(A n B) = P(A) * P(B|A)
Dependent Multiplication Rule
P(X=x) = (1-p)x-1p
Geometric Notation
σx = √np(1-p)
Binomial Standard Deviations
Standard Deviation Transformation: σA+Bx
σA+Bx = |B| * σx when a is a constant