Sampling Methods

bias

biased samples are more likely to produce some outcomes than others 

convince

too easy to collect

volunteer response sample

self - elected sample of people who respond from general appeal

simple random sampling (SRS)

a sample of n subjects selected in a way that every possible sample of the same size n has the SAME CHANCE of being chosen

simple random sample 

stratified sample

subdivide the population into at least two different subgroups (strata) so the subjects within the same subgroup share the same characteristics. Then draw a sample from each subgroup - proportionally with respect to the size of population 

stratified sample 

cluster sample

divide the population area into naturally occurring sections (clusters) then randomly select some of those clusters and choose ALL the members from the selected clusters 

cluster sampling 

systematic sampling

select a starting point and then select every k^th element in the population

systematic

multistage sample

collection of data by using some combination of basic sampling methods

bad sampling frame

when attempting to list all members of a population, some subjects are missing 

under coverage

the sampling frame is missing groups from the population or the groups have smaller representation in the sample than in the population 

non-response bias

some part of the population chooses not to respond, or subjects were selected and not able to be contacted

response bias

responses given are not truthful

wording and order

the way a question or statement is worded may be misleading or influencing to give a particular response