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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.
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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
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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.
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what does p(A) equal from an a priori viewpoint?
P(A) = [Number of events classifiable as A]/[Total number of possible events]
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what does p(A) equal from an a posteriori probability viewpoint?
p(A) = [Number of times A has occurred]/[Total number of occurrences]
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p(A or B) = ? (general rule)
- p(A or B) = p(A) + p(B) - p(A & B)
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Two events are mutually exclusive if ...
both cannot occur together.
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p(A or B) = ? (mutually exclusive)
p(A or B) = p(A) + p(B)
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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)
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a set of events is exhaustive if...
the set includes all of the possible events
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when 2 events P and Q are exhaustive and mutually exclusive P + Q = ?
P + Q = 1.00
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p(A & B) = ?
p(A & B) = p(A) * p(B|A)
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p(A & B) = ?, when events A and B are mutually exclusive events.
p(A & B) = 0
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two events are independent if ...
the occurrence of one has no effect on the probability of occurrence of the other.
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p(A & B) = ?, when A and B are independent.
p(A & B) = p(A) * p(B|A) = P(A) * P(B)
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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)
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p(A & B) = ?, if A and B are dependent events.
p(A & B) = p(A) * p(B|A)
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p(A & B & C & ...& Z ) = ?, if events are all dependent.
p(A & B & C & ...& Z ) = p(A) * p(B|A) * p(C|AB) * ...* p(Z|ABC...)
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 (summation)
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( 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)
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Percentile point (equation for computing percentile point
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= ?
Percentile rank
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or (mean of a sample or population respectively)
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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
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- P = probability of one of the two possible outcomes of a trial
- Q = probability of the other possible outcome
- N = number of trials
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