Poststratification is a weighting procedure that adjusts the weights of respondents so that the weighted sample distribution is the same as some known population distribution. That is, the sums of the poststratified-adjusted weights of the respondents are equal to known population totals for certain subgroups of the population. Poststratification improves precision of survey estimates by reducing their mean square error and enhances the comparability of survey data with other surveys, particularly when comparing estimates from the same survey over time.
The geography and U.S. history assessment students were poststratified separately, so that the weights of both sets of assessments will aggregate to the national population totals (i.e., represent the full U.S. student population). In addition, the assessments were split into two "reporting populations," R2 and R3, for the poststratification step.