(2-1)
A basic statement of probability.
(2-2)
Probability of the union of two events.
(2-3)
Conditional probability.
(2-4)
Probability of the intersection of two events.
(2-5)
Bayes’ Theorem in general form.
(2-6)
An equation that computes the expected value (mean) of a discrete probability distribution.
(2-7)
An equation that computes the variance of a discrete probability distribution.
(2-8)
An equation that computes the standard deviation from the variance.
(2-9) Probability of r successes in n trials
A formula that computes probabilities for the binomial probability distribution.
(2-10)
The expected value of the binomial distribution.
(2-11)
The variance of the binomial distribution.
(2-12)
The density function for the normal probability distribution.
(2-13)
An equation that computes the number of standard deviations, Z, the point X is from the mean
(2-14)
The exponential distribution.
(2-15)
The expected value of an exponential distribution.
(2-16)
The variance of an exponential distribution.
(2-17)
Formula to find the probability that an exponential random variable, X, is less than or equal to time t.
(2-18)
The Poisson distribution.
(2-19)
The mean of a Poisson distribution.
(2-20)
The variance of a Poisson distribution.