Module 4: Data Classification

     Hello all, this week we learned about different ways to classify data and how it can affect the truth of the data you are trying to display in your map. The below maps depict the distribution of people aged 65 years or over compare the equal interval, quantile, natural breaks, and standard deviation data classifications. The first set of map comparisons show the data based on percent of the population and is not normalized by area. The second set of map is based on the total population and normalized by square miles. 

The program used for this map compilation was ArcGIS. Out of all the maps below, if i were to present this map to an audience, I would most likely present natural breaks in population count normalized by area. My reasoning is because it highlights the true clusters of seniors taking into consideration population density. Most if not all of the others under the percentage map sets will make the reader think there are way more seniors by land out in the country areas than there really are thus making them believe they should provide more resources than is actually needed to those areas. Standard deviation of population count could also be useful though I think this more shows how areas deviate from the county average thus it highlights some areas that aren’t really part of the distribution information we are looking for.