I chose to analyze the data set on men’s body fat measurements where the statistical data was provided by the Journal of Statistics of Education website. This specific data collection consists of different types of measurements of fat, ranging from their overall body fat to specifying measurement size of certain body parts, such as the abdomen, hip, knee, wrist, etc. From the metadata, I wanted to see if there was a relationship between body fat and certain sizes of a particular body part. If so, what kind of relationship?
Using Silk, a data visualization generator website, I was able to test my hypothesis using a line graph. Originally, I wanted to use a scatter plot graph, but it restricted me plotting two columns showing the only one set of data. The line graph can be misleading because the magnitude between each point shows that there’s some sort of relationship between all the each individual data point, but in fact that there’s no relationship between let’s say participant 156 and participant 87.
From the data visualization attached above, we can see that as the those who has more body fat tend to have a larger abdomen, as evident in the upward trend under abdomen. However, what I discovered was that body fat doesn’t necessarily have an affect every single part of your body. When I graphed all 252 men’s wrist size, I was able to see that there was a constant line, averaging around 18.2. One could easily assume that one’s wrist size could have a direct relationship to the how much body fat one has. With this visualization it was a lot easier to see the kind of relationship body fat has to the size of other body parts. Similar to what Nathan Yau said in “Data Points: Visualization That Means Something,” “With visualization, when you know how to interpret data and how graphical elements fit and work together, the results often come out better than software defaults.” If one were to view it from the excel sheet, it is definitely a lot hard to spot this trend.
Really nice job!