3. Stratified random sampling: Data is divided into various sub-groups (strata) sharing common characteristics like age, sex, race, income, education, and ethnicity. A random sample is taken from each strata. The advantages are- it assures representation of all groups in the population needed. The characteristics of each stratum can be estimated and comparisons can be made. It also reduces variability from systematic sampling. The limitations are that it requires accurate information on proportions of each stratum; also stratified lists are expensive to prepare.