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Stats sampling quiz vocab
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44 Terms
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Population
Complete set group of individuals/items with a common study of interest for a statistical study
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Sample (Representative)
Small, manageable number of subjects that represent a larger population
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Parameter
Numerical summary of a population; used to describe the entire population being studied.
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Statistics
Numbers that summarize, gather, and decide data from a sample
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Census
complete count of the people living in a country with their info: (job/age/gender)
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Simple Random Sampling
Every member of the population has a known and equal chance of being chosen at random: (names out of hat)
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Stratified Random Sampling
Divide the population into groups by shared characteristic and randomly select from each: (age, occupation, gender)
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Cluster Sample
Divide population into clusters and whole cluster gets picked for sample; must be HETEROGENOUS/DISTINCT
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Systematic Sampling
Select samples in numbered intervals: (every 4th person, 1st person does not count)
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Convenience Sampling
Choose who/what is easiest to reach for sample
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Voluntary Response Sample
Only those who want to participate for sample
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Multistage Sampling
Uses multiple sampling methods subsequently; must be different to be considered multistage
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Bias
Systematic tendency to affect particular outcomes over another; can only be reduced, not eliminated
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Voluntary Response Bias
Participate when they want to = over/under representation; usually surveys
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Undercoverage
When some participants are left out/not enough people in sample = under representation
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Non-Response Bias
Chosen individuals cannot be reached, or do not want to respond; we need different perspectives = under representation
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Response Bias
People LIE due to sensitive/confusing topics = under representation
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Random Sampling
Best method to reduce bias
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Observational Study
Observe individuals w/o manipulation/intervention
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Experiment
a test under controlled conditions made to demonstrate a known truth or validate a hypothesis ; develop direct CAUSE & EFFECT relationship
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Response Variable
Dependent variable ( y )
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Explanatory Variable
Independent variable ( x )
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Experimental unit
Person/object assigned randomly to a treatment
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Factor
Variables controlled during experiments to determine their effects on response variables
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Treatment
Administered to experimental units
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Level
Amount/magnitude of treatment given; treatment w/ more than 1 factor applied
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Treatment Group
Group receiving treatment
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Control
CONSTANT experimental factor; effects do NOT change with treated participants
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Control group
Group that does NOT receive any treatment
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Single Blind
Participants unaware of whether they received treatments
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Double Blind
Participant AND researchers do not know who received treatment
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Placebo
Appears as an active treatment = 0/NO treatment and is FAKE
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Placebo Effect
Effects seen in people receiving no treatment
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Confounding Variable
3rd variable influences both x & y variables; effect on dependent/response/y-variable cannot be distinguished from more than 1 x variables
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Lurking Variable
Unknown variable that is not controlled for; usually in independent/explanatory/x-variable & observational study
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Survey
Set of ?s to gather specific data from population samples
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Randomization
Randomize into specific treatments to reduce differences and favoring one experimental condition over another
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Blocking
Group similar participants to reduce bias between groups
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Replication
Repeating experiments w/ similar characteristics for similar results
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Experimental Units (Subjects)
Performed on people, items, things; Humans = samples/subjects
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Response Variable
Dependent/y-variable to be measured
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Explanatory Variable (Factor)
independent/x-variable that can be controlled, manipulated, changed
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Treatment
Manipulation (or experimental condition) implemented by the experimenter
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Blinding
Subjects/Researchers do NOT know what treatments are assigned to which experimental unit (subjects)