Statistics and Statistical Programming (Winter 2017)/R lecture outline: Week 5

as promised, we'll be adding much less each week.

first, lets make two datasets:
 * 1) Lets download this dataset of births in North Carolina: http://www.openintro.org/stat/data/nc.RData (documentation is here)
 * 2) Lets also continue to work with rivers. I want to first add some random noise: new.rivers <- rivers: rnorm(n=length(rivers), mean=100, sd=100)


 * unpaired t-test with two vectors: just t.test
 * works with the rivers examples in the same way
 * we can also do it with birthweight boys and girls in the nc.dataset by splitting into two vectors
 * paired t-tests with t.test(paired=TRUE):
 * i'm not going to walk through doing it by hand this week. i trust you can translate the equations in the book into R at this point
 * unpaired t-test with the formula notation: t.test(mpg ~ am, data=mtcars) # manual versus automatic transmission
 * anova: aov, we'll be talking about anova later!
 * returns an aov object. we can save that and then use the summary function to give us more useful information
 * we can see that the results are very similar with the two group example!

extra good things to know:


 * if statements: i use them often in a function
 * lets make a version of my river modification code above that only adds positive numbers
 * for loops: for (name in list) {}
 * next is useful