Population, Sample, Bias (Section 1.2-1.6

people choose to be in the sample

voluntary response

data from every individual

census

assigns treatment

experiment

easy to reach individuals from the population

convenience sample

some groups rarely selected

undercoverage

inaccurate to a survey question

response bias

everyone has an equal chance of being selected

random sample

an individual can’t be contacted or refused to participate

nonresponse

every group of n individuals in the population has an equal chance of being selected

simple random sample (SRS)

ranges from 1 to N

Label

use a random number generator to obtain n different integers from 1 to N

randomize

choose the individuals with the labels that correspond to the integers selected by the random number generator

select

different random samples of the same size from the same population produce different estimates

sampling variability

separates the population into non-overlapping groups

strata

selects a sample by choosing an SRS from each stratum and combining the SRS into one overall sample

stratified random sampling

a group of individuals in the population that are located near each other

cluster

selects a sample by randomly choosing clusters and including each member of the selected clusters in the sample

cluster random sapling

two variables are associated that their effects on a response variable cannot be distinguished from each other

confounding

measures an outcome of a study

response variable

predicts changes in a response variable

explanatory variable

responds favorably to any treatment

placebo effect

double blind experiment

compares the effects of other treatments

control group

the object to which a treatment is randomly assigned

experimental unit

a treatment that has no active ingredient but is otherwise like other treatments

placebo

use subjects to create roughly equivalent groups

replication