exam 2 Data

Complement

Subset of outcomes not part of event A

Simple event

Event with a single outcome that can only happen in one way

Mutually exclusive

Set of events that cannot occur at the same time

Collectively exhaustive

Set of events where one must occur

Certain event

Event sure to occur, like rolling a value greater than 0 on a fair die

Impossible event

Event with no chance of occurring

Priori probability

Probability based on prior knowledge of possible outcomes

Empirical probability

Probability based on observed data, not prior knowledge

Subjective probability

Probability differing from person to person

Simple probability

Probability of a simple event with equally likely outcomes

Joint probability

Probability of two or more events occurring

Marginal Probability

an event consists of a set of joint probabilities

Counting Rule 1

Determines possible outcomes for mutually exclusive and collectively exhaustive events

• If any one of K different mutually exclusive and collectively exhaustive events can occur on each of n trails, the number of possible outcomes is equal to K^n

Counting Rule 2

is a more general version of the first counting rule and allows the number of possible events to diff from trial to trial.

• K1,K2,K3

Counting Rule 3

Computes the number of ways a term can be arranged in order

• n!= (n)(n-1)...(1): where n! Is called n factorial, and 0! Is defined as 1

Counting Rule 4

Number of ways of arranging x objects selected from n objects in order

• nPx = n!/ (n-x)!

Counting Rule 5

Number of ways of selecting x objects from n objects irrespective of order

• nCx = n!/x!(n-x)!

Permutations

Ways a subset of items can be arranged in order

Combinations

Ways x items can be selected from n items irrespective of order

Discrete Variable

Mutually exclusive list of possible numerical outcomes with probabilities

Z-score

Value in a normal distribution

• z= x -μ / σ

Uniform distribution

Values equally distributed between smallest and largest values

Exponential distribution

Values from zero to positive infinity, right-skewed with mean > median

Continuous probability

Varies by the shape of the area under the curve

Normal Distribution

Is not only symmetrical, but bell-shaped, a shape that (loosely) suggest the profile of a bell

Contingency table (reading it)

How many political party are there?

2 or more

empirical rule- when the value fall within +1 standard deviation it is

Approximately 68.26%

the values fall within {2 standard deviations of the mean it Is

• Approximately 95.44%

the values fall within {3 standard deviations of the mean it is

• Approximately 99.73%