Weekly 8

Reflect on what data is included or omitted from your Project 2, and in what ways you became more intimate with or distanced from the participants or subject by measuring, quantifying, or visualizing the data.

There was so much data provided for crime in LA that we omitted the vast majority of it. Our project, like the Middletown authors, tried to provide a general overview of the data (with the categories of vandalization, assault, and theft), but tells a limited story because of that effort to pare down and simplify. I'm reminded of the Porter's mention that "data" can refer to numbers that are found, because if someone looked at our data visualization and not the LA data as a whole, an entirely different set of questions might arise.

For me, as we went through the bigger set of data, it definitely raised several questions, including:

Also, as Mimi explained, who collects data is also super important: she used the example of hate crimes, and there’s no leap of logic necessary to assume that the same is happening with this other data: this information is a) what got reported, not what happened, and b) what was recorded. We thought there might be something interesting happening with the average ages of the victims, and the entire time I could hear my high school stats teacher groaning in dismay. One insane outlier can distort the average and thus the story, and I definitely felt conflicted just having that and not also the mode and median.