11/15 Update

Because I was having a lot of trouble finding the asthma data, I thought that I would take a break and start working on my ozone information for California.  I went onto the EPA website under the outdoor air quality data section and was able to find a link to download daily data for ozone within California during the year 2010 (which I have decided to use since my population density data is from 2010).  I was able to download the data, however I am not sure how to actually download it into GIS or how to sort through it since the data is coming from everyday in 2010.  I will have to find someway to categorize the data so that it is concise but not overwhelming, and does not leave any important data out.  Maybe I should take the averages per month?

11/8 Update

I have made a map composed of the population densities of each of the counties in the state of California.  I used a graduated color scale to show the differing densities.  A lighter color indicates a lower population density while a dark color represents a higher population density.  I know that I should include the county labels on the map, but there is some overlapping so I am having some trouble figuring out how to solve this problem so that the labels of the counties are visible but do not make my map look too crowded.  My next step is going to be working on importing my asthma data, and this may mean settling for emergency room visits of asthma related cases rather than actual numbers of asthma cases per county as I am having trouble finding the specific information I am looking for. 

11/1 Update

Due to the problems I encountered with trying to add asthma data, I have fallen a little behind schedule, and plan to regroup.  I have decided that for this week, I will continue to follow my plan and incorporate the population densities per county in California as a layer, and will add in my asthma data at a later date when I have found a reliable and accurate source of county data.  In order to get a better representation of the population densities per county, I will create the layer based of quantities and displayed the layer in terms of graduated colors.  Therefore, the more saturated/deeper the color, the higher population density that the county has, and the less saturated/lighter the color, the less population density that the county has.  This gradual color symbology, will the display of the connection between the population and my other variables of air quality and asthma cases more clearly and will make it easier to see the correlations between the variables.

10/25 Update

I have started to import my data and create data layers within GIS.  I have created one layer for the state of California, and another layer that outlines the counties within California.  I tried to start importing the asthma data per county, however I was having a lot of trouble adding the layers to my map from ArcGIS online.  With that being said, I am going to give it another chance but if I continue to have trouble with it, I am going to have to do more research and look elsewhere for other sources to obtain my asthma data from.