The implementation of my project is divided into two parts:
First, I wanted to analyse, if there are any social factors which are dominating the areas 'Starbucks' are located. And if so, what are these in detail?
Second, after determing the specific factors, which seem to correlate with the location of the 'Starbucks', are there other areas for placements of further 'Starbucks'? Has 'Starbucks' occupied all the suitable parts of Vancouver or are some of them left?
For the first part of my analysis I had to manipulate the data. I have already chosen the categories of the data I wanted to look at. Moreover, I had to determine the composition of each factor. Which are necessary and helpful factors, which of them are useless for my project?

For my analysis I wanted to create different maps all showing the impacts of one special social factor.
At least I chose the following factors:

• Rate of Unemployment: One of my questions was, if the Rate of Unemployment in one Census Tract of Vancouver influences the decision of locating a new 'Starbucks'. If the Rate is high, won't there be so many 'Starbucks', because people can't afford the money for coffees? Or is 'Starbucks' integrated in everybody's life and also affordable for everybody? 
• Rate of Income: A following question was, if the level of income influences the distribution of 'Starbucks'. Can only people with a higher level of income afford this kind of coffee or are these people rejecting this kind of lifestyle? - For this Rate I created groups of Income.
• Women/Men Ratio: It was thought as a kind of a joke but I wondered if  a majority of women or men influences the locations of  'Starbucks' in a Census Tract. I converted the absolute numbers of women and men of a Census Tract into percentages - and was surprised getting the result!
• Rate of Non-Canadians: Have people of different countries another relationship to coffee? Do Canadians love coffee of 'Starbucks' most? Or is coffee most preferred by other nations (maybe not knowing  this company before - like me)? - For the following analysis I converted the absolute number of Non-Canadians of a Census Tract into percentage.
• Main Group of Age: Do younger people consume coffee most? Do the elderly reject this kind of coffee and prefer 'old-fashioned' coffee? Consume people in the middle of their ages coffee on their way to work? - For the following analysis I joined different groups of age, because the units of the original data are too small.
• Main Group of Households: Is 'Starbucks' located where more single or more family Households are settled? Are singles the typical consumers of coffee?
• Population Density: Does a higher Population Density implicate a higher percentage of consumer? - To answer this question I calculated the persons per squarekilometre.
• Rate of the Service Sector: Does a higher Rate of the Service Sector mean more people are in this area during the day? And as a consequence consuming more coffee and influencing the locations of 'Starbucks'? - I divided all the labor divisions into three categories: The first, second and third sector and calculated the percentage of each of them.

I extracted the essence of those relationships (e.g. the main group of age in a Census Tract where the most 'Starbucks' are located is between 30 and 40 years) and made them to a principle influencing the distribution of 'Starbucks'. In my opinion the factors above give an overview of the criteria influencing the locations of 'Starbucks'. Nevertheless, I know that a high correlation can also be a result of coincidence...


Carthographic Model