- We want to use continuous ratio data in order to see the range of the values of the lines that intersect each axis. If we used categorical data, we would not be able to plot them in a specific order and all the lines for each category would converge into one point when it hits the respective axis. We can see a similar effect of this problem on the example graph in the lab assignment sheet. There is a color map applied to time, so we can see how the values for each axis relate to the time of day. For example, cooler temperatures tend to occur early in the morning, whereas warmer temperatures occur later in the day. We can also see how uncorrelated temperature is to conductance. However, it’s much harder to examine correlations at specific dates because they converge for their respective day. Thus, we can see that if we had a categorical axis, all the lines would converge to a single point, and it would be much harder to determine correlations among the other axes with the categorical one.
- I chose conductance, which is ratio data. It is continuous because each data point lies on a continuous scale (it can be any possible value) between the max and min conductance values. If conductance were restricted to certain values, it would be discrete. I chose the color scale interpolateYlOrRd because it is a sequential color map. Therefore, the color map is great to display the range of continuous conductance data in one direction from smallest to largest. I wanted to use a scale that didn’t start with a white color, so the smallest conductance data would be more visible on a white background.