
A random sample is defined as a sample selected from the population by a process that ensures that ___(1)___, and ___(2)___.
 (1) each possible sample of a given size has an equal chance of being selected
 (2) all the members of the population have an equal chance of being selected.

Sampling with replacement is defined as...
a method of sampling in which each member of the population selected from the sample is returned to the population before the next member is selected

sampling without replacement is defined as ...
a method of sampling in which the members of the sample are not returned to the population before the subsequent members are selected.

what does p(A) equal from an a priori viewpoint?
P(A) = [Number of events classifiable as A]/[Total number of possible events]

what does p(A) equal from an a posteriori probability viewpoint?
p(A) = [Number of times A has occurred]/[Total number of occurrences]

p(A or B) = ? (general rule)
 p(A or B) = p(A) + p(B)  p(A & B)

Two events are mutually exclusive if ...
both cannot occur together.

p(A or B) = ? (mutually exclusive)
p(A or B) = p(A) + p(B)

p(A or B or C ...or Z) = ? (addition rule with more than 2 mutually exclusive events)
p(A or B or C ...or Z) = p(A) + p(B) + p(C)+...+p(Z)

a set of events is exhaustive if...
the set includes all of the possible events

when 2 events P and Q are exhaustive and mutually exclusive P + Q = ?
P + Q = 1.00

p(A & B) = ?
p(A & B) = p(A) * p(BA)

p(A & B) = ?, when events A and B are mutually exclusive events.
p(A & B) = 0

two events are independent if ...
the occurrence of one has no effect on the probability of occurrence of the other.

p(A & B) = ?, when A and B are independent.
p(A & B) = p(A) * p(BA) = P(A) * P(B)

p(A & B & C & ...& Z) = ?, when events A, B, C,... and Z are independent.
p(A & B & C & ...& Z) = p(A) * p(B) * p(C) *...* p(Z)

p(A & B) = ?, if A and B are dependent events.
p(A & B) = p(A) * p(BA)

p(A & B & C & ...& Z ) = ?, if events are all dependent.
p(A & B & C & ...& Z ) = p(A) * p(BA) * p(CAB) * ...* p(ZABC...)

(summation)

( cumf: number of scores that fall below upper real limit of each interval)
(cumulative percentage: indicates the percentage of scores that fall below real limit of each interval)

Percentile point (equation for computing percentile point

= ?
Percentile rank

or (mean of a sample or population respectively)

the binomial distribution is a probability distribution that results when the following five conditions are met:
(1) ____
(2) ____
(3) ____
(4) ____
(5) ____
 (1): there is a series of N trials
 (2): on each trial, there are only two possible outcomes
 (3): on each trial, the two possible outcomes are mutually exclusive
 (4): there is independence between outcomes of each trial
 (5): the probability of each possible outcomes on any trial stays the same from trial to trial.
 *When these requirements are met, the binomial dist tells us each possible outcome of N trials and the probability of getting each of these outcomes

 P = probability of one of the two possible outcomes of a trial
 Q = probability of the other possible outcome
 N = number of trials

