Unit 3.1 Terms

Probability Experiment

A action or trail, through which specific results are obtained

Outcome

Result of a single trail of a probability experiment

Sample Space

is the set of all possible outcomes of a probability experiment

Event

A subset of sample spaces

Simple event

has one outcome

Compound event

constits for two or more outcomes

Empirical Probability (Statistical)

Uses results from conducting or observing a procedure a large amount of times (what actually happened)

Classical Probability (Theoretical or Actual)

Uses sample spaces to determine the numerical Probability that an event will happen. (what should happen)

Law of Large Numbers

The more an experiment is repeated, the closer the results get to its Theoretical probability

The Probability of any event E is (P(E)):

number of ways E can occur / total number of outcomes in the sample space

The probability of any event E is a:

Number between 0 and 1, inclusively

If an event E cannot occur it is a:

Probability of 0

If an event E is certain, it is a:

Probability of 1

The sum of the probabilities of the outcomes in the:

Sample Space is 1

There are only _ outcomes for any event

2

P(not E) is often written as:

P(~E)

Tree Diagrams:

a visual display of an experiment consisting of all possibilities

Tree Diagrams constist of ________________ per branch

Multi-step probabilities of events with different unequal values

Tree Diagrams are often used to _____________________

compute probabilities of events with different unequal values

Fundamental Counting Principle

If one event can occur “x” ways and another event can occur “y” ways then the events can occur together x*y ways

Conditional Probability:

is the probability of an event occurring, given that another event has already happened

Denoted P(B|A) read as: ”____”

Probability of B, given A

P(A and B) = P(A) * P(B)

Independant Events Formula

and means?

Multiply

If an experiment is with replacement:

Independent

Two events, A and B are _______ if the probability is affected by the outcome of the other

Dependant

(A and B) = P(A) * P(B|A)

Dependant event formula