#################### # Module 7 - Lab # 7/1/2014 #################### ## Part A # Bike Lanes Dataset: BikeBaltimore is the Department of Transportation's bike program. # https://data.baltimorecity.gov/Transportation/Bike-Lanes/xzfj-gyms # Download as a CSV (like the Monuments dataset) in your current working directory # 1. Using tapply(): # (a) Which project category has the longest average bike lane? # (b) What was the average bike lane length per year that they were installed? # 2. (a) Numerically [hint: `quantile()`] and (b) graphically [hint: `hist()` or `plot(density())`] # describe the distribution of bike "lane" lengths. # 3. Then describe the bike length distributions after stratifying by # i) type then ii) number of lanes [hint: tapply, boxplot] ## Part B # Download the CSV: http://biostat.jhsph.edu/~ajaffe/files/indicatordeadkids35.csv # Via: http://www.gapminder.org/data/ # Definition of indicator: How many children the average couple had that die before the age 35. # 4. Plot the distribution of average country's count across all years. # 5.(a) How many entries are less than 1? # (b) Which array indices do they correspond to? [hint: `arr.ind` argument in `which()`] # 6. Plot the count for each country across year in a line plot [hint: `matplot()`]