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response variable
measures an outcome of a statistical study
explanatory variable
may help explain or predict changes in a response variable
factors
explanatory variables that are manipulated and may cause a change in the response variable
levels
different values of a factor
treatment
a specific condition applied to the items or individuals in an experiment
experimental unit
the item or individual to which a treatment is assigned (often called subjects when human beings)
retrospective
past or current data
prospective
data into future
confounding variable
impacts results of an experiment or observational study
experiment
suggests cause-and-effects relationships
observational study
suggests an association between variablesanr
random sample
randomly selected portion of a population that allows us to generalize our results to the entire population
simple random sample (SRS)
every individual is equally likely to be selected
every possible group is equally likely to be selected
systematic random sample
choose a random kth starting point from a list of entire population
select every nth student until your sample is filled
only can be done with an organized list
stratified random sample
separate population into smaller subgroups
select some from ALL
guaranteed to have subgroups represented
cluster random sample
select ALL from some
easier to accomplish since people are “closer together”
convenience sample (poor sampling method)
surveying people that are all close by
voluntary response sample (poor sampling method)
no one is selected, all responses come from volunteers
bias
consistent over/underestimation of true value
undercoverage
people in a population are not able to be selected for some reason
response bias
people feel pressure to respond a certain way (i.e. anonymity)
nonresponse bias
people who were selected don’t respond or cannot be contacted