Sun Sep 15 13:15:43 2013
Due Date: September 19, 2013 Total Points: 30
1 The following ten observations, taken during the years 1970-1979, are on October snow cover for Eurasia in units of millions of square kilometers. Follow the instructions and answer questions by typing the appropriate R commands.
Year Snow 1970 6.5 1971 12.0 1972 14.9 1973 10.0 1974 10.7 1975 7.9 1976 21.9 1977 12.5 1978 14.5 1979 9.2
a. Create a data frame from these data. (2)
y <- as.numeric(1970:1979)
sqkm = as.numeric(c(6.5, 12, 14.9, 10, 10.7, 7.9, 21.9, 12.5, 14.5, 9.2))
dfSnow <- (data.frame(a = y, b = sqkm))
names(dfSnow) <- c("Year", "Snow")
b. What are the mean and median snow cover over this decade? (2)
mean(dfSnow$Snow)
## [1] 12.01
median(dfSnow$Snow)
## [1] 11.35
c. What is the standard deviation of the snow cover over this decade? (2)
sd(dfSnow$Snow)
## [1] 4.391
d. How many Octobers had snow cover greater than 10 million km\( ^2 \)? (2)
length(which(dfSnow$Snow > 10))
## [1] 6
2 The data set rivers contains the lengths (miles) of 141 major rivers in North America.
a. What proportion of the rivers are shorter than 500 miles long? (2)
tRivers <- length(rivers) #Total number of rivers
sRivers <- length(which(rivers < 500)) #Numbers of rivers shorter than 500 miles long
(sRivers/tRivers) * 100 #Percentage of rivers shorter than 500 miles long
## [1] 58.16
b. What proportion of the rivers are shorter than the mean length? (2)
tRivers <- length(rivers) #Total number of rivers
smRivers <- length(which(rivers < (mean(rivers)))) #Numbers of rivers shorter than mean length of all rivers
(smRivers/tRivers) * 100 #Percentage of rivers shorter than mean length of all rivers
## [1] 66.67
c. What is the 75th percentile river length? (2)
quantile(rivers, probs = c(0.75))
## 75%
## 680
d. What is the interquartile range in river length? (2)
IQR(rivers)
## [1] 370
3 Consider the SSN.txt file from http://myweb.fsu.edu/jelsner/data/SSN.txt. The file contains monthly sunspot numbers for since 1851.
a. Import the data into R. (4)
loc <- "http://myweb.fsu.edu/jelsner/data/SSN.txt"
ss <- read.table(loc, header = TRUE)
b. Create a histogram of the September sunspot numbers. (2)
require(ggplot2)
## Loading required package: ggplot2
ggplot(ss, aes(x = ss$Sep)) + geom_histogram(binwidth = 5) + xlab("September Sunspot Activity")
c. Create a boxplot of the June sunspot numbers. Label the axis. (4)
boxplot(ss$Jun, ylab = "June Sunspot Activity")
d. Create a scatter plot placing the June sunspot numbers on the horizontal axis and September sunspot numbers on the vertical axis. Label the axes. (4)
ggplot(ss, aes(x = ss$Jun, y = ss$Sep)) + geom_point() + xlab("June Sunspot Activity") +
ylab("September Sunspot Activity")
