I felt most of the rules were already intuitive to me. For instance, the fact that you don’t want to use too many “pure” or “strong” colors (rule), especially not wanting to put those kinds of colors together - these colors are only supposed to be used sparingly and to accentuate certain things. Tufte used the example of how in real life, extreme events are rare (such as in geography), and thus, these extreme colors should also only be used rarely, in conjunction with whatever extreme or rare events of whatever context the colors are being used in. However, I did find some issues with this reasoning, because of the definition of extreme - by the definition of extreme, it must be rare, since if there were many instances, it would not be extreme. At the same time, there shouldn’t be a parallel drawn with colors since we can actively choose color palettes whereas we cannot form mountains or crevasses as easily.

I found Tufte’s point about making color scales to be interesting. He gave the example of values to show scale, or ROYGBIV to show scale, and implied that it is more natural for humans to intuitively understand value scales compared to ROYGBIV scales, perhaps because we have to learn the order of ROYGBIV (although this order occurs in nature, such as in rainbows). I don’t think this is true in my own experience. While value scales look better in my opinion, I don’t find ROYGBIV scales more difficult to interpret - weather maps often are ROYGBIV-scale-like, and the recent COVID tracking maps from the NY Times were also not value-based.

I found Few’s article to not be that interesting. I liked how he broke down his grievances with the Batesman paper, specifically how the examples they choose he felt, were leading toward a certain result. This is something that is super important in research - how to frame your experiments to not just confirm your hypothesis or your preexisting beliefs. However, the actual conclusions - that sometimes plain charts are better than embellished charts, and vice versa is self explainatory in itself in my opinion. It really depends on the content that is to be displayed, it depends on the audience, too. Of course, if the data is simple, then an embellishment can drive home that simple point, but if the data is complicated and hard to comprehend in itself, embellishments are just noise.