Wikipedia defines "MAUP" (Modifiable Areal Unit Problem) like this:
https://en.wikipedia.org/wiki/Modifiable_areal_unit_problem
The modifiable areal unit problem (MAUP) is a source of statistical bias that can significantly impact the results of statistical hypothesis tests. MAUP affects results when point-based measures of spatial phenomena are aggregated into districts, for example, population density or illness rates. The resulting summary values (e.g., totals, rates, proportions, densities) are influenced by both the shape and scale of the aggregation unit.
For example, census data may be aggregated into county districts, census tracts, postcode areas, police precincts, or any other arbitrary spatial partition. Thus the results of data aggregation are dependent on the mapmaker's choice of which "modifiable areal unit" to use in their analysis. A census choropleth map calculating population density using state boundaries will yield radically different results than a map that calculates density based on county boundaries. Furthermore, census district boundaries are also subject to change overtime, meaning the MAUP must be considered when comparing past data to current data.
See Attachment
A great description with screenshots can be found here:
http://gispopsci.org/maup/
This is an extremely important GIS topic that those of us who perform Spatial Analysis should at least be familiar with.
A related real world application of this concept can be found in the Political redistricting concept known as "Gerrymandering".
See this article for more on that topic:
The following link is no longer available. To access this information, copy the title found in the url into the search tool on the top nav bar, or try searching for key words in the post. https://li360.pitneybowes.com/s/question/0D58000003XkuFVCAZ/maps-and-gerrymandering-and-why-we-should-care