elementary statistics ulm Exam 2

independent variable

explanatory variable predictor

dependent variable

response variable

regression

statistical methos used to describe the nature of a relationship between values, liner/nonlinear, positive/negative

lurking variable

data that is not shown

probability

chance of an event occurring

probability experiment

a chance process that leads to well defined results

outcome

the result of the single trial of a probability experiment

sample space

the set space of all outcomes in a probability experiment

event

the outcome of a probability experiment

types of probability

classical empirical subjective

empirical probability

calculated based on data

how to find classical probability

number of ways to get it over the amount of total outcomes

unusual event

probability between 0% and 5%

mutually exclusive or disjoint

two event that cannot occur at the same time

Probability range

0≤P(x)≤1

Addition Rule Formula

P(AorB)=P(A)+P(B)-P(Aand B)

Fundamental Counting Principal Purpose

used to count the total number of outcomes

How to find Fundamental Counting Principal

Possible outcomes for each event multiplied together

when probabilities are equal we say the outcomes are

equally likely

complement

set of outcomes in the same space that are not among the outcomes of the event itself

Rule of Complementary Event

P(E)+P(Ec)=1

Classical Probability formula

times you can get it/ total things you can get

independent events

A and B do not effect the probability of each other

when to use multiplication rule

when 2 events are independent the probability of both occurring

multiplication rule formula

P(AandB)=P(A)P(B)

Permutation

numbers of ways you can arrange things

permutation formula

nPr=(n!)/(n-r)!

0!=?

1

combination

selection of distinct objects without regard to order

combination formula

nCr

special permutaion

some are duplicates

special permutation formula

t!/dupe1*dupe2

conditional probability

probability with a certain condition

conditional probability formula

P(F/E)=(P(E+F)/(P(E))

at least one rule

P(at least one)=1-P(None)