Name:
Andrew ID:
Collaborated with:

This lab is to be done in class (completed outside of class if need be). You can collaborate with your classmates, but you must identify their names above, and you must submit your own lab as an knitted HTML file on Canvas, by Sunday 11:59pm, this week.

This week’s agenda: getting familiar with basic plotting tools; understanding the way layers work; recalling basic text manipulations; producing histograms and overlaid histograms; heatmaps.

Fastest 100m sprint times

Below, we read in a data set of the fastest times ever recorded for the 100m sprint, in men’s track. (Usain Bolt may have slowed down now … but he was truly one of a kind!) We also read in a data set of the fastest times ever recorded for the 100m, in women’s track. Both of these data sets were scraped from http://www.alltime-athletics.com/m_100ok.htm (we scraped it in spring 2018; this website may have been updated since).

sprint.m.dat = read.table(
  file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/sprint.m.dat", 
  sep="\t", quote="", header=TRUE)
sprint.w.dat = read.table(
  file="http://www.stat.cmu.edu/~ryantibs/statcomp/data/sprint.w.dat", 
  sep="\t", quote="", header=TRUE)

Data frame and apply practice

Plot basics

n = 50
set.seed(0)
x = runif(n, min=-2, max=2)
y = x^3 + rnorm(n)
plot(x, y, type="p")

plot(x, y, type="l")