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Compare data from multiple areas, and use the contrasting population densities to make observations about those areas. For example: if the city of Boonesville includes 60,000 people overs its 8 square miles, then its population density is 7,500/square mile. You can see that the population density of Auburn is far higher than the population density of Boonesville. Consider whether you can use this difference to draw any conclusions about the two cities. Even if you calculate the population density of an area as dense as a large city, the resulting figure will not tell you much about the differences between individual neighborhoods. You may need to find the density for various area scales in order to fully understand a place. Calculate the projected population growth for a given area, then compare the current population density with the predicted future density. Look for census data from the past, and try comparing past population densities with the current figure. Try to understand how a place has changed and will change. It is simple and straightforward to calculate population density in this way, but it may not reveal more intricate details about an area. This is highly dependent upon the size and type of the area for which you are calculating population density. The formula sometimes says more about smaller, densely-inhabited areas than it does about larger areas that include both inhabited and uninhabited land. Say that you calculate the population density of a county that is home to a huge amount of open land and national forest, but also to a very large city. The population density of the county at large will not tell you much about the density of the city: the actual space where people live. Remember that population density is just an average. It may not correspond exactly to the population count of an area. If not, consider why. Try calculating the density for a smaller area within the original area. Make predictions about an area given when you know about high and low population densities. For instance, areas with high population densities tend to have higher crime rates and higher prices for housing and goods. Low-density areas tend to feature more agriculture, and they often include more wilderness or open space. The conclusions that you draw about a given area or areas will depend upon your purposes. Think about how you can make this data insightful.
Compare population density. Try including population growth. Be aware of the limitations. Think about the data.