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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

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