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

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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 (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