Statistics Ch 9

if individual outcomes are uncertain, but there is nonetheless a regular distribution of outcomes in a large number of repetitions.

of any outcome of a random phenomenon can be defined as the proportion of times the outcome would occur in a very long series of repetitions.

Mathematically describe the outcome of random processes. They consist of two parts:

• 1) S = Sample Space: a set, or list, of all possible outcomes of a random process.
• An event is a subset of the sample space.

2) A probability for each possible event in the sample space S.

1) Probabilities range from 0 (no chance of the event) to 1 (the event has to happen).

For any event A, 0 ≤ P(A) ≤ 1

2) The probability of the complete sample space must equal 1.

P (sample space) = 1

3) The probability of an event not occurring is 1 minus the probability that does occur.

P(A) = 1 – P(not A)

• 4) Two events A and B are disjoint if they have no outcomes in common and can never happen together. The probability that A or B occurs is the sum of their individual
• probabilities.

P(A or B) = “P(A U B)” = P(A) + P(B)

This is the addition rule for disjoint events.

P(A or B) = “P(A U B)” = P(A) + P(B)

deals with data that can take on only certain values. These values are often integers or whole numbers

• contains an infinite number of events. They typically are
• intervals of possible, continuously-distributed outcomes.