Stats sampling quiz vocab

Complete set group of individuals/items with a common study of interest for a statistical study

Small, manageable number of subjects that represent a larger population

Numerical summary of a population; used to describe the entire population being studied.

Numbers that summarize, gather, and decide data from a sample

complete count of the people living in a country with their info: (job/age/gender)

Every member of the population has a known and equal chance of being chosen at random: (names out of hat)

Divide the population into groups by shared characteristic and randomly select from each: (age, occupation, gender)

Divide population into clusters and whole cluster gets picked for sample; must be HETEROGENOUS/DISTINCT

Select samples in numbered intervals: (every 4th person, 1st person does not count)

Choose who/what is easiest to reach for sample

Only those who want to participate for sample

Uses multiple sampling methods subsequently; must be different to be considered multistage

Systematic tendency to affect particular outcomes over another; can only be reduced, not eliminated

Participate when they want to = over/under representation; usually surveys

When some participants are left out/not enough people in sample = under representation

Chosen individuals cannot be reached, or do not want to respond; we need different perspectives = under representation

People LIE due to sensitive/confusing topics = under representation

Best method to reduce bias

Observe individuals w/o manipulation/intervention

a test under controlled conditions made to demonstrate a known truth or validate a hypothesis ; develop direct CAUSE & EFFECT relationship

Dependent variable ( y )

Independent variable ( x )

Person/object assigned randomly to a treatment

Variables controlled during experiments to determine their effects on response variables

Administered to experimental units

Amount/magnitude of treatment given; treatment w/ more than 1 factor applied

Group receiving treatment

CONSTANT experimental factor; effects do NOT change with treated participants

Group that does NOT receive any treatment

Participants unaware of whether they received treatments

Participant AND researchers do not know who received treatment

Appears as an active treatment = 0/NO treatment and is FAKE

Effects seen in people receiving no treatment

3rd variable influences both x & y variables; effect on dependent/response/y-variable cannot be distinguished from more than 1 x variables

Unknown variable that is not controlled for; usually in independent/explanatory/x-variable & observational study

Set of ?s to gather specific data from population samples

Randomize into specific treatments to reduce differences and favoring one experimental condition over another

Group similar participants to reduce bias between groups

Repeating experiments w/ similar characteristics for similar results

Performed on people, items, things; Humans = samples/subjects

Dependent/y-variable to be measured

independent/x-variable that can be controlled, manipulated, changed

Manipulation (or experimental condition) implemented by the experimenter

Subjects/Researchers do NOT know what treatments are assigned to which experimental unit (subjects)