Quantitative Data Classification

QUESTION 5 (5)

Since you are a journalist, putting together maps of housing cost in Vancouver, which classification method would you choose for your audience and why?  What if you are a real estate agent preparing a presentation for prospective home buyers near UBC? Are there ethical implications for your choice of classification method? This data is from 2011 – it is now 2017 – should you even be using this data? Discuss.

As a journalist, I would want to classify the data with natural breaks because I would want to show the most accurate representation of the data. Using natural breaks, the system divides the data based on its distribution, reducing the amount of error.

As a real estate agent, I would choose manual breaks because I would want my clients to think of Vancouver as an affordable city. Using manual breaks, it would also be possible to show my clients the most affordable houses/apartments based on their budget.

I believe that there are definitely ethical implications that come with choosing one method of data classification over another. For example, a journalist would most likely use the most accurate representation of the data however depending on the story they trying to portray, I could chose a method that might . But as a real estate agent, I may want to report on or the story they want to tell and the biases of that story. This being said, a real estate agent would want to portray the data in the least intimidating way possible to their client. They would choose the method of classification that would best suit the client and what they are looking for according to price range or even wealth/socioeconomic class of the neighbourhood.

Housing affordability in Vancouver has changed in the past 6 years as the real estate market has grown, so using the 2011 data would not be representative of housing affordability in Vancouver today.

 

Housing affordability:

 

It is to be noted that affordability is not always a good indicator of livability. This being said, areas that are more livable tend to have more expensive housing costs.