Probability & Non-Probability Sampling Techniques

simple, systematic, stratified, cluster random sampling

probability sampling techniques < (4,)

purposive, quota, convenience, snowball (sampling)

non-probability sampling techniques < (4,)

random selection

any member of population has equal chance of being selected as a sample

simple random sampling

define population, list all members, select sampling by employing an adequate procedure

simple random sampling

portion of whole population is selected in an unbiased way

fishbowl technique

simple random sampling AKA

systematic random sampling

planned strategy for selecting members

systematic random sampling

all members of population known, listed in unbiased way, then select every nth person

systematic random sampling

example: 5000 popu. / 50 samples = 100

every 100th person is chosen

stratified random sampling

specific groups will have a sufficient number of representatives, participants in grp selected at random

stratified random sampling

subsets are sampled separately so important minorities or subgrps are represented in the total

stratified random sampling

desirable when the various subgrps are likely to respond differently

strata

specific groups in sampling

cluster random sampling

select members of your sample in grps rather than using separate individuals

cluster

where subjects within may resemble one another

purposive sampling

uses a criteria

quota sampling

gathers data until researchers arrive at their required number of participants

convenience sampling

only those who are willing and available only

snowball sampling

use of referrals

multistage sampling

combination of 2+ sampling techniques, but mix not allowed

- random + random

- nonprob + nonprob