In this lab one thing that I learned in this lab was the different between Census Tracts (CT's) and Census Dissemination Areas (DAs). A pro to using CT’s is that they are small so they are relatively stable. They generally have populations between 2,500 and 8,000 persons and are good for metropolis areas. DA’s are usually smaller than CT’s are also relatively stable. They contain populations of 400-700 people. It could be more beneficial to use a DA over a CT if you want very precise data because DAs are “the smallest standard geographic area that all census data are disseminated.” DA’s also cover all the territory of Canada. A con to using DAs is there is often suppression in them due to their smaller size in order to reduce confidentiality concerns. CT’s have a lower chance of being suppressed, however they have the lowest resolution and are only available for largest centers.
Another important thing I learned in this lab is the difference and importance of using varying classification methods for data. In this lab I observed 4 methods specifically which are found in the map linked below. Depending on which method is used, the viewer's interpretation of the map could be greatly altered.
4 data classification methods map: lab4dataclass
No data:
Throughout this lab, I also learned the significance of census areas that have 'no data'. Sometimes this is because of data suppression. There are three scenarios in which data will be suppressed/not published for certain census areas. The main reason for suppressing data is to not disclose the information of any certain individuals. In general, for quantitative values, if the number of records in a calculation is less than four then the statistic will be suppressed. However two other reasons for suppression is if there is a large outlier, or if the max of the absolute values falls below a threshold parameter. Sometimes data is also not available in an area because it is under it's own jurisdiction, for example First Nation reserves. An additional reason for areas with no data could be because of homelessness or people refraining from answering censuses.
Cost of Housing and Housing Affordability:
The goal of this lab was to create some maps that compare the shelter cost of Metro Vancouver to Montreal. The produced maps are linked below. The one entitled "housecostVM" is used to display the range of homes in different cost brackets. I had an error in creating this map because the break values are not all the same. This causes the map to be a bit misleading due to the fact that the side by side comparison using the same colors are not the same range of value on each map. However, they are close enough that it still allows the viewer to understand the great discrepancy in housing costs between the two cities. The second map, titled "affordability", is again comparing the housing costs of the two cities, however this one uses an affordability ratio rather. An affordability ratio is used to compare the affordability of houses between markets. The ratio looks at the house price to income ratio. This is widely used in evaluating housing markets. The housing markets are rated from what is considered affordable to what is considered extremely unaffordable. Housing affordability ratio is usually a better indicator of actual affordability of housing than housing cost alone. This is largely because it uses the 'median multiple' which connects median house prices to that of median household incomes.
Maps created comparing shelter cost: housecostVM affordability
Data Source: Census Canada Cartographic boundary files http://data.library.ubc.ca/ http://www.demographia.com/dhi.pdf