Just like comparing my other two proportions together, I decided to break up the gender and the age instead of having them together so a better picture of the relationship can be seen. I also decided to use the age group of 16-19 year olds again because most human beings are pretty much developed by these ages. Below are the regression plot for both males and females.
As you can see that the data seems to look closely exact to each other. Though the male’s data seems to have a more linear pattern. Because of the data jumping around everywhere, this can be because of human error. I know this because we are looking at an age group and it wouldn’t make sense for someones length of their foot measure 16.5 centimeters and their forearm be at 27 centimeters, that would be a pretty funny looking 16-19 year old.
As you can see all the data for both genders with this age groups jumps around the residual line. But, the males seem to have more of a pattern going on which having more of their point of the line itself acting more linear than the females. But for females there seems to be a pattern as well. As X increases between the measurements of around 22 to 26 the relationship is close together.