Housing Affordability— Vancouver and Montreal affordabilityVM
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This map clear shows the housing affordability in Vancouver and Montreal, by comparing the median income to housing cost and family earnings in a certain census tract. This is a more effective way of accessing housing affordability, than just rely on housing cost, because the families who earn more highly possible live in more expensive house. According to the 11th Annual Demographia International Housing Affordability Survey, it categorized the following affordability: Severely Unaffordable 5.1 & Over, Seriously Unaffordable 4.1 to 5.0, Moderately Unaffordable 3.1 to 4.0, Affordable 3.0 & Under. The rating is aim to monitor the affordability of the two cities and to alert the government have to control the cost through the Macroeconomic regulation. It is obvious that the map indicate Montreal is much more affordable when taking median house cost and familial earning into account. After all, most census tracts in Vancouver are shown in this map as severely unaffordable.
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This map shows the data for housing coast in Vancouver in different classification method – Equal Interval, Natural Breaks, Manual Breaks and Standard Deviation. The data shows differently with different method of classification. The equal interval classification method is by creating breaks to divided the range into equal sized classes, including the outliers and the extreme values of the dataset, which doesn’t consider the distance between the data points. The drawbacks of this method is when the outlier are too large or too small from the majority, then a majority of points that are observed within a close distance. In the map of Vancouver, we can see that the equal interval method skews the data so that it appears that the majority of the houses are affordable because there are some outliers at the very expensive end of housing costs. The standard deviation method classifies the data by the standard deviation from the mean. The disadvantage of this method are that readers will hard to understand the map, might cause confusion the the purpose of the map nor its legend. The second map is using the natural breaks, this method takes into account the distance between data points and places the breaks in relation to that distance. However, in terms of the legend, since the numbers are automatically calculated by the computer, it will not always be rounded. Finally, the manual breaks method allows the users to “customized” their own breaks. It is significant for the users to considering all of the ethical implications of the display of data, and to choose the most suitable method to classify the data.