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24 terms

Stats

STUDY
PLAY
Simple random sampling
everyone has an equal chance of being chosen
Stratify
separating the group by a characteristic that you think will influence the answer
Stratified random sampling
random sampling within each group
Cluster
after deciding subgroups, randomly selecting a group and surveying the entire group
Systematic
creating a system in order to randomly pick people
Convenience sample
includes individuals who are convenient, not a good representative
Voluntary response sample
group of individuals invited to respond
Response bias
if questions in a survey are weighted one way
Non-response bias
results are not well represented because people choose not to respond
Undercoverage
when a group of the population is missing from your sample
randomizing
protects from the influences of all features of the population by making sure that on average the sample looks like the rest of the population
Parameter
the thing you want to learn about
Statistic
the thing you find about the parameter
Sampling Frame
everyone available to be framed
Sample
who ended up being chosen
Observational Studies
looking at data, drawing conclusions
Prospective
Identify subjects and follow them for some pre-determined time to gather data
Retrospective
analyze data that has already been collected
Experiments
To determine cause/effect relationships
Random assignement of subject/units to treatments is required
Random selection of subjects is not required (can volunteer)
To draw conclusions about the relationships against variables
Factor in designing experiments
what's being manipulated/controlled
Treatments
Multiply levels x factors
Blocking
break subjects into groups by characteristic that could possibly be influenced in the experiment
Blind
when subject doesn't know what theyre getting
Double bind
when the the subject nor the person administering the experiment know what they're getting/giving