ISDS exam 2

probability

A number that describes how likely it is that an event will occur

experiment

process that leads to one of several possible outcomes

sample space (S)

the set of all possible outcomes of an experiment

event

subset of outcomes of an experiment

Exhaustive Events

Events that include all possible outcomes

Mutually Exclusive Events

Events that cannot occur at the same time.

union of two events (A u B)

the event consisting of all events in both A or B

The Intersection of two events (A∩B)

event consisting of all outcomes in A and B

The Complement of an event A (A^C)

Refers to the event "not A"

sum of probabilities of any list of mutually exclusive and exhaustive events

P(S)=1

Two Events are Independent If...

P(A|B) = P(A) or P(B|A) = P(B)

characteristics of normal distributions

-symmetrical

-mean, median and mode all equal

-only 1 mode

-no skewness or kurtosis

-areas under the curve are fixed (we know what % of scores is above or below a given value)

Standard Normal Distribution

A normal distribution with a mean of 0 and a standard deviation of 1.

z-score represents

the number of standard deviations a random variable is from its mean

probability sample

a sample in which every element in the population has a known statistical likelihood of being selected

non-probability sample

any sample in which little or no attempt is made to get a representative cross section of the population

Goal of inferential statistics

detect meaningful and significant patterns in research results

sampling distribution is normal if

(1) the population is normal

(2) the sample size is large (n≥30) (Central Limit Theorem)

(3) both

How does sample size effect standard error?

the larger the sample size, the smaller the standard error

the shape of the distribution is approximately normal if both

npi>5 and n(1-pi)>5