Block sampling technique used in a sequential series of selections. For example auditing. In a block sampling, Sampling risk can be reduced by selecting a large number of blocks. Stratified sampling is done by selecting subgroups or strata which can represent the population within the whole sample. In block sampling, we have to select a population or subject randomly whereas in Stratified sampling the selection of population or subject is based on a specific qualification.

Example:

Let say, for an experiment we need to gather 20 apples. Tree no 1 has 14 apples whereas tree no 2 has 6 apples.14 apples would be considered as the first block and the last 6 apples would be considered as the second block, to see the differences caused by them being from different trees.

A college campus has 40 % non-teaching and 40% teaching stuff. Instead of doing a random sample of 100 from the whole population, where we could potentially get 30 non-teaching and 70 teaching staffs stratify the population into strata by category and take a proportional random sample from teaching and non-teaching stratum.