May 20, 2016
Georgetown's "new gen ed" (since 2010):
The three primary skills have (inter-woven) components that are explicitly addressed in most sections of the course.
The structure of a thing is
Structure guides interpretation.
Outlining: a typical exercise in reading for structure.
[From the Iliad:]
Achilles wasted no time. Leaving his spear Propped against a tamarisk And holding only his sword, he leaped from the bank He struck over and over …
Fish fleeing from a dolphin’s huge maw
Hide by the hundreds in the harbor’s crannies
But the dolphin devours whatever it catches.
Likewise the Trojans beneath the riverbanks.
Tenor (literal) | Vehicle (symbolic) |
---|---|
Achilles | Dolphin |
Trojans | Fish |
Sword | Huge maw |
Riverbank | Crannies of the harbor |
The map is structure-preserving:
Consider
Often explicitly treated. In class, instructor might ask: "What's a good critical engagement question about this passage?"
Sub-skills are:
Non-traditional aspects:
"Elementary statistics isn't really a course in mathematics.
It's a course about judgement."
—Daniel Kaplan, Macalester College
We read, argue and write about data.
(Typically in the form of an R data data frame!)
Understanding of data is driven by employing the Read skill in each of its four aspects:
"Watch your process: be aware of when you are applying each sub-skill."
R reads for structure, with the str()
function:
str(iris)
## 'data.frame': 150 obs. of 5 variables: ## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... ## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ... ## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ... ## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ... ## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
with(iris, str(Species))
## Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
Tell the story of the data as it stands? (Numerical and graphical summaries.)
"Structure guides interpretation." Appropriate tools chosen by mean of variable analysis:
help(iris)
Favor | Oppose | |
---|---|---|
No | 375 | 199 |
Yes | 243 | 59 |
Comment: "Folks who don't own a gun are more likely to oppose capital punishment than those who do own a gun, because 199 non-owners oppose capital punishment whereas only 59 gun-owners do."
Two Data Analysis Reports:
Process:
Rubrics-based grading.
tigerstats
. Includes links to many other resources relevant to this talk.