statistics vocabulary

Convenience Sampling

choosing individuals from the population who are easy to reach results in a convenience sample

why are convenience samples bad

often underrepresents the data

voluntary response sampling

a sampling method that consists of people who choose to be in the sample by responding to a general invitation

why are voluntary response samples bad

people who feel strongly about an issue, particularly people with strong negative feelings, are more likely to take the trouble to respond

random sampling

a sampling method that involves using a chance process to determine which members of a population are included in the sample

random sampling methods

simple random samples (SRS) stratified random samples cluster random samples systematic random samples

bias

would consistently underestimate or consistently overestimate the value you want to know when the study is repeated many times

simple random samples (SRS)

a sample chosen in such a way that every group of n individuals in the population has an equal chance of being selected as the sample

sampling variability

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

stratified samples

the population is divided into smaller groups, subpopulations (strata), then another random sampling method is used to create the sample

cluster samples

population is divided into smaller groups, clusters, that are then randomly selected for the sample

systematic samples

researchers select members of the population at the same intervals (k) determined in advance

undercoverage

some members of the population are less likely to be chosen or cannot be chosen for the sample

nonresponse

when an individual chosen for a sample cant be contacted or refuses to participate

response bias

there is a consistent pattern of inaccurate responses to a survey question

population

entire group of individuals we want info about

census

collects data from every individual in the population

sample

subset of individuals in the population from which we collect data

confounding

occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other

response variable

measures the outcome of the study

explanatory variable

may help predict or explain changes in a response variable