University – Data Types, Summary Statistics,
and Probability Principles
relative frequency (empirical) probability based on experimentation or historical data
ex: consumer preference for soft drinks
dr. pepper = .067
interpret as probability of a consumer preferring dr. pepper
subjective probability based on JUDGEMENT
ex: company working on deal
vp #1 believes there's a .7 chance of it going through
vp#2 believes there's a .4 chance
event collection of sample points
probability of events = sum of probability of all sample points
complement of event all sample points NOT IN event A
P(A) + P(A)^c = 1
, addition laws probability of event A, B or A and B occuring
P(AuB) = P(A) + P(B) - P(AnB)
Union event containing ALL sample points in A and B
both circles AND middle of venn diagram
intersection all sample points in both A AND B
only middle of venn diagram
nominal data names indicating characteristic
ex: NYSE, NASDAQ
ordinal data can be ordered/ranked
ex: gold, silver, bronze
interval data quantitative AND can be ranked BUT is a fixed unit of measurement
ex: SAT scores, credit score
ratio data quantitative AND can be ranked BUT is a fixed unit of measurement AND the
ratio is meaningful
categorical data (qualitative) identify characteristics of element
ex: gender, marital status
ALSO: zip code, phone number