Editing Stratified sampling (section)

==Advantages==
The reasons to use stratified sampling rather than [[Simple random sample|simple random sampling]] include<ref name=":0">{{Cite news|title = 6.1 How to Use Stratified Sampling {{!}} STAT 506|url = https://online.stat.psu.edu/stat506/lesson/6/6.1|newspaper = Pennstate: Statistics Online Courses|access-date = 2015-07-23}}</ref>
# If measurements within strata have a lower standard deviation (as compared to the overall standard deviation in the population), stratification gives a smaller error in estimation.
# For many applications, measurements become more manageable and/or cheaper when the population is grouped into strata.
# When it is desirable to have estimates of the population [[Statistical parameter|parameters]] for groups within the population – stratified sampling verifies we have enough samples from the strata of interest.
If the population density varies greatly within a region, stratified sampling will ensure that estimates can be made with equal accuracy in different parts of the region, and that comparisons of sub-regions can be made with equal [[statistical power]]. For example, in [[Ontario]] a survey taken throughout the province might use a larger sampling fraction in the less populated north, since the disparity in population between north and south is so great that a sampling fraction based on the provincial sample as a whole might result in the collection of only a handful of data from the north.