Section 4.4

1

a <- c(TRUE, TRUE, TRUE, FALSE, FALSE)
b <- matrix(2,4,6,8)
c <- list("my", "list")

length(a)
## [1] 5
length(b)
## [1] 24
length(c)
## [1] 2

2

a <- c(TRUE, TRUE, TRUE, FALSE, FALSE)
b <- matrix(2,4,6,8)
c <- mtcars

length(a)
## [1] 5
length(b)
## [1] 24
length(c)
## [1] 11

Section 5.1

1

summary(mtcars)
##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000
plot(mtcars$mpg,mtcars$disp, xlab="MPG", ylab="disp")

Section 5.2

1

Olympic Data Downloaded

2

olympic_data <- read.csv("olympic_athletes.csv")

athletes2 <- data.frame(olympic_data$athletes[,c("name", "sport")])


write.csv(athletes2, "olympic_athletes_name_sports.csv")

Section 5.3

1

weight <- (olympic_data$Weight)

weight <- weight[is.na(weight)]


weight_min <- min(weight)
weight_med <- median(weight)
weight_sd <- sd(weight)

weight_stats <- list(weight_min, weight_med, weight_sd)

2

season_stats <- list(olympic_data$Season)
table(season_stats)
## season_stats
## Summer Winter 
##   4137    863