Explanatory Analyses

In this swiss dataset, we have 47 observations of 6 variables. The variable names are: Fertility, Agriculture, Examination, Education, Catholic, Infant.Mortality. In the interest of time, space, and mental exhaustion, let’s just pick one to explore!

Let’s see, maybe R can randomly pick something for us…

A random number generator gives us: 1. That corresponds to Fertility, cool! Now while it would be fun to do the rest of this assignment with a random variable, we can’t really make comments on plots and such without knowing it in advance. Let’s plot this variable!

Hmm. A couple of those municipalities are way up there in this right-skewed distribution, specifically. As it stands currently, this variables has a mean of 10.98 and a standard deviation of 9.62. But since it’s so skewed, the median (8) is the better indicator of its center. It would be worth doing a log transformation to get a more normally distributed variable as we see below. We would definitely want to work with this transformed variable in any modeling.

And finally, a pairwise scatterplot to give us an idea of correlative relationships to explore in the future. It’ll have to be tabled (heh) for now.

Pairwise comparisons of swiss variables