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Survey Stratification Research

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Survey Stratification Research

Survey stratification is used when dividing up the overall population into smaller subpopulations, to help see different patterns in the data. Survey stratification should be used either before collecting the data or when you have data from different sources; but should always be used with consideration of which will have an effect on the results. 
There are many ways to view survey stratification in tables and graphs. For example, if the researcher was looking at whether there is a correlation between the amount of pollution and the number of people becoming ill, you could put the data into a scatter graph. However, you can stratify the sample into ages, and make all the points of people under 20 with a triangle, all the people aged 20-50 with a square and all the people above 50 with a circle. This can make different patterns of data visible in order to gain better information.
Survey stratification is effective at gaining more precise data and can obtain key characteristics in the population. However, it cannot be used in every study and the researcher must select a subpopulation for all the participants. It can be very challenging to find a selection of subgroups that fit all the participants. However, if the researcher does not manage this, the data may be deemed unreliable.

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