Editing 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:
# Lets download this dataset of births in North Carolina: http://www.openintro.org/stat/data/nc.RData ([https://htmlpreview.github.io/?https://github.com/andrewpbray/oiLabs-base-R/blob/master/inf_for_numerical_data/inf_for_numerical_data.html documentation is here])
# 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