## 12. Appendix 1
## 12.1 R Packages for Windows
## 12.2 Contributed Documents and Published Literature

## 12.3 Data Sets Referred to in these Notes
## 12.4 Answers to Selected Exercises
## Section 1.6
## 1.  
plot(distance~stretch,data=elasticband)
## 2. (ii), (iii), (iv)
plot(snow.cover ~ year, data = snow)
hist(snow$snow.cover)
hist(log(snow$snow.cover))
## Section 2.7
## 1. The value of answer is (a) 12, (b) 22, (c) 600.
## 2. 
prod(c(10,3:5))
## 3(i)  
bigsum <- 0;  for (i in 1:100) {bigsum <- bigsum+i }; bigsum
## 3(ii)  
sum(1:100)
## 4(i)   
bigprod <- 1;  for (i in 1:50) {bigprod <- bigprod*i };  bigprod
## 4(ii) 
prod(1:50)
## 5. 
radius <- 3:20;  volume <- 4*pi*radius^3/3
sphere.data <- data.frame(radius=radius, volume=volume)
## 6. 
sapply(tinting, is.factor)
  sapply(tinting[, 4:6], levels)
sapply(tinting[, 4:6], is.ordered)
## Section 3.9
## 2.   
par(mfrow = c(1,2))
    plot(Animals$body, Animals$brain, pch=1, 
      xlab="Body weight (kg)",ylab="Brain weight (g)")
 plot(log(Animals$body),log(Animals$brain),pch=1,
   xlab="Body weight (kg)", ylab="Brain weight (g)", axes=F)
brainaxis <- 10^seq(-1,4) 
bodyaxis <-10^seq(-2,4)
axis(1, at=log(bodyaxis), lab=bodyaxis)
axis(2, at=log(brainaxis), lab=brainaxis)
box()     
identify(log(Animals$body), log(Animals$brain), labels=row.names(Animals))   
## Section 7.9
## 1.  
x <- seq(101,112) or x <- 101:112
## 2.   
rep(c(4,6,3),4)
## 3.  
c(rep(4,8),rep(6,7),rep(3,9)) or rep(c(4,6,3),c(8,7,9))
   mat64 <- matrix(c(rep(4,8),rep(6,7),rep(3,9)), nrow=6, ncol=4)
## 4.  
rep(seq(1,9),seq(1,9)) or rep(1:9, 1:9)
## 6.  (a) Use  summary(airquality) to get this information.
   (b) 
airquality[airquality$Ozone == max(airquality$Ozone),]
   (c) 
airquality$Wind[airquality$Ozone > quantile(airquality$Ozone, .75)]
## 7. 
mean(snow$snow.cover[seq(2,10,2)])
  mean(snow$snow.cover[seq(1,9,2)])
## 9. s
summary(attitude); summary(cpus)
## 10.  
mtcars6<-mtcars[mtcars$cyl==6,]
## 11.  
Cars93[Cars93$Type=="Small"|Cars93$Type=="Sporty",]