The Truthful Art (Ch9 & Ch10) : - MariaAguilarV/JMM-622-Infographics-and-Data-Visualization GitHub Wiki

In Chapter 9 of the Truthful Art, Cairo talks about the relationships between variables and how to illustrate them. It is important to notice that not all variables are related, we might see a tendency in a scatter plot, but we have to analyze what are the real causes of those variables; for instance, he illustrates the example of chocolate related with happiness and Nobel prizes or IKEA furniture; but these are disparate associations, if we thing about them, they might be related to the wealth of a country, if people have more income, then probably, they will buy more chocolate or more IKEA furniture. As the author explained in previous chapters, it is important to find a clear explanation to the association between variables. Even more, Cairo summarizes some criteria to evaluate these relationships and the use of some concepts as the correlation coefficient and the coefficient of determination. The relationship between two variables is usually illustrated in a scatter plot where it is easy to perceive the strength of the relation, if the data points are closer to the trend line then the association between variables is stronger (if the trend line is linear, we talk about correlation). Besides seeing the relationship between variables, there is also a formula which allows us to find specific values just by replacing the variables.

Then, Cairo talks about representing data in maps and covers the basics of proportional symbol maps, choropleth maps and other kinds of maps that illustrate data in various creative ways. I found this chapter very useful, not only because the importance in data visualization, but for my daily life, I didn’t know that there were different types of maps based on the projection of their properties as shape, area, angles, distance, and direction. And how the Mercator map has become the standard in online tools where they preserve continental shapes but not local angles, for example, we can see that Alaska looks as big as Brazil. So, it is important to think about what we want to display and what type of map would be accurate when we want to illustrate our data in a map.

I find maps one of the best ways to illustrate data because they help readers locate themselves in the space, thus the story will have more impact on them. These weeks, The Oscars has been a popular topic, and I just found an article form The Washington Post titled "The Oscars in six charts and maps", and their first map said “Where to set your film if you want an Oscar” - pretty interesting headline, I thought! They showed the following map where we can see where the Oscar winner movies were filmed on. If this data would have been illustrated in a table, maybe it wouldn’t be as impactful as it is. Although this article is from 2015, it is interesting how the authors used other infographics to tell interesting stories as the tendencies of gender and age for Oscar winners and Oscar dresses. (The whole article can be found here)