Download Sampling Theory • sample space set of all possible outcomes of a

Section 4.2
1
Sampling Theory
• sample space
set of all possible outcomes of a chance experiment
• event
set of one or more outcomes from the sample space
• probability model
method for assigning probabilities to the outcomes
in a sample space
• disjoint events
events which have no outcomes in common, i.e., can
never occur simultaneously
Rules of Probability
1. Probability P(A) of an event A lies between 0 and 1.
2. P(S) = 1 where S is the entire space.
3. P(A does not occur) = 1 – P(A).
4. If A and B are disjoint events, then
P(A or B) = P(A) + P(B).
Section 4.2
2
Random variables
• random variable
variable whose value is the outcome of a random
phenomenon
If there are only finitely many possible outcomes of a
random variable, assign probabilities to each of these;
then, the probability of any event is the sum of the
probabilities of its individual outcomes.
If events consist of interval ranges of values of a
random variable (like a normally distributed variable)
which is described by a certain density curve, the
probability of an event is the area under the density
curve over that interval.