http://www.ck12.org Chapter 2. Visualizations of Data
New Zealand, Estonia, and Sweden (circled in yellow) have much lower paper recycling rates than their glass rates,
and Austria (circled in green) is an example of a country with a much lower glass rate than their paper rate. These
data points are spread away from the rest of the data enough to make the ellipse much wider, therefore weakening
the association between the variables.
Explanatory and Response Variables
In this example, there was really no compelling reason to put paper on the horizontal axis and glass on the vertical.
We could have learned the same information about the plot if we had switched those variables. In many data sets,
however, the variables are often related in such a way that one variable appears to have an impact on the other. In
the last lesson, we examined countries that are the top consumers of bottled water per person. If we compared this
to the amount of plastics that these countries are disposing in landfills, it is natural to think that a higher rate of
drinking bottled water could lead to a response in the amount of plastic waster created in that country. In this case
we would refer to the bottled water consumed as theexplanatory variable(also referred to in science and math as
theindependent variable). The explanatory variable should be placed on the horizontal axis. The amount of plastic
waste is called theresponse variable(also referred to in science and math as thedependent variable), which be
placed on the vertical axis. There are most likely other variables involved, like the total population, recycling rate,
and consumption of other plastics, so we are not implying that the bottled water consumption is the sole cause of
change in plastic waste, and without actual data it is difficult to even comment on the strength of the relationship,
but it makes sense to look at the general relationship in these terms. It is very natural to think of this as a cause and
effect relationship, though you will learn in a later chapter that it is very dangerous to assume such a relationship
without performing a properly controlled statistical experiment.
Line Plots
The following data set shows the change in the total amount of municipal waste generated in the United States during
the 1990’s.