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Raw Data
Info with a context that has been gathered but not processed

data
raw data cleaned up so it can be analyzed

individuals (subjects, experimental units)
entities on which data is collected

variable
charasteristics measured on individuals

observation (row of data, case)
measurement of a variable or collection of variables

Distribution of a Variable
possible values of a variable and how often each possible value occurs

normal distrubtion
bell curve

descriptive statistics
numbers and graphs that represent the data

inferential statistics
techniques used to collect data from a small group that is used to conclude things about a larger group

sample
 the
 small group used to find out things about a larger group

population
the larger group the the smaller group is used to draw conslusions about

representitive
ex: sample must be "representative" of the population
things in sample have to have similar charasteristics to those in the population
distribution of variables in sample needs to be similar to distribution of variables in population

census
when data collected from every individual in the population

statistic
numerical summary of a sample

parameter
numerical summary of a population

categorial (qualitative) variable
produces categorial data, assigns label or category to individual (ex: eye color, blue)

quantitative variable
 assigns meaningful # to an individual
 (ex: persons height)

nominal
no natural ordering of values from least to greatest (ex:eye color)

ordinal
ordering values from least to greatest but when it does not make sense to subtract them (ex: cancer stages IIV)

interval
 natural order of least to greatest
 differencing (subtracting) makes sense
 making a ratio (dividing) does not make sense
 "0" does not mean "absence of"

ratio
 least to greatest natural ordering
 differencing makes sense
 ratio makes sense
 "0" means "absence of"

observational study
observes or questions individuals w/o imposing any conditions on them

sampling method
the choice of what individuals are going to represent the population

randomized experiment (designed experiment)
imposes something on individual then measures responses under imposed conditions

disadvantage of observational study
can only claim association between variables

adv of randomized experiement
can often determine cause and effect

