Categories: All - conditional - independent - experiment - probability

by Krystal Starks 13 years ago

640

Chapter 3 Probability

In the realm of probability theory, several key concepts and rules help to understand and compute the likelihood of various events. Independent events are those where the occurrence of one event does not influence the probability of another.

Chapter 3 Probability

Range of probabilities rule

the probability of an event E is between 1 and 0, inclusive.

Counting

Combinations

a selection of r objects from a group of n objects without regard to order and is denoted by nCr. The # of combinations of r objects selected from a group of n objects is

nCr= n!

(n-r)!r!

Question # 23, pg. 179

A lottery has 52 numbers. In how many different ways can 6 of the numbers be selected? (Assume that order of selection is not important.)

=52 C 6

=20,358,520

Permutations

an ordered arrangement of objects. The # of different permutations of n distinct objects is n!

Question # 20, pg. 178

Eight people compete in a downhill ski race. Assuming that there are no ties, in how many different orders can the skiers finish.

=40,320

FundamentalCounting Rule

if 1 event can occur in m ways and a second event can occur n ways. The # of ways the two events can occur in sequence is m*n. This rule can be extended for any # of events occurring in sequence.

Question #41, pg. 180

A password consists of two letters followed by a five-digit number. How many passwords are possible if (a) there are no restrictions and (b) none of the letters or digits can be repeated?

(a) 26*26*10*10*10*10*10= 67,600,000

(b) 26*25*10*9*8*7*6= 19,656,000

Probability

Law of Large Numbers

as an experiment is repeated over and over, the emperical probability of an event approaches the theoretical (actual) probability.

Subjective Probability

results from intution, educated guesses, and estimates.

Multiplication Rule

Keyword "AND"

at least one
Problem J
ConditionalProbability

the probability of an event occurring, given that another event has already occurred. The conditional probability of event B occurring, given that event A has occurred, is denoted by P(B/A).

Problem C
DependentEvents

events that are not independent are dependent.

Problem A
IndependentEvents

if the occurence of 1 event does not affect the probability of the other evert. Two events A &B are independent if P(B/A)= P(B) or if

P(A/B)=P(A)

Probelem H

Probability Experiment

an action, or trail, through which specific results (counts, measurements, or responses) are obtained.

Event

a subset of the dample space. May consist of one or more outcomes.

Simple Event

an event that consists of a single outcome.

Sample Space

the set of all possible outcomes of a probability experiment.

Outcome

the results of a single trail in a probability experiment.

Addition Rule

Keyword "OR"

Non-Mutually Exclusive

If A and B are not mutually exclusive then,

P(A or B) = P(A) + P(B) - P(A and B)

Problem F
Mutually Exclusive

Mutually Exclusive Events are events that cannot occur at the same time.

If A and B are mutually exclusive,

P(A and B) = 0

If A and B are mutually exclusive,

P(A or B) = P(A) + P(B)

Problem B

Basic Probability

Complement of Event E

the set of all outcomes in a sample space that are not included in event E.

Problem E
Empirical Probability

is based on observations obtained from probability experiments.

P(E)= Frequency of event E = f

Total frequency h

Problem I
Classic Probability

is used when each outcome in a sample space is equally likely to occur.

P(E)= number of outcomes in event E

total # of outcomes in sample space

Problem G