Introduction

This is a quiz examining different R coding language using a dataset containing speed and distance of cars.

Data

This code loads the cars dataset from the datasets package. This is a special package - by loading the datasets package, we automatically load a number of toy datasets used for teaching R. Run this code chunk to load the data in your environment.

library(datasets)
head(cars)
##   speed dist
## 1     4    2
## 2     4   10
## 3     7    4
## 4     7   22
## 5     8   16
## 6     9   10

head() is a good function to quickly visualize your data.

# 1. compute the mean speed of the car

avrspeed <- mean(cars$speed)

avrspeed
## [1] 15.4
# 2. compute the max distance of the car

max(cars$dist)
## [1] 120
maxdis <- max(cars$dist)

maxdis
## [1] 120
# 3. add a new variable to the cars dataset called "mult" that is the product of speed and distance

cars$mult <- (cars$speed * cars$dist)

# 4. compute the minumun of this new column

min(cars$mult)
## [1] 8
minmult <- min(cars$mult)

minmult
## [1] 8
# 5. create a NEW dataset where all rows in which speed is less than 10 to 0

cars2 <- subset(cars, cars$speed < 10)

# 6. compute the mean of speed in this new dataset

mean(cars2$speed)
## [1] 6.5
avrspeedcars2 <- mean(cars2$speed)

avrspeedcars2
## [1] 6.5

Visualization

Go back to the original cars dataset for these visualizations.

# 7. plot a histogram of speed 

hist(cars$speed,
     main = "Histogram of speed",
     xlab = "Speed",
     col = "red",
     freq = TRUE)

# 8. plot a histogram of distance and add the title "Car Distance"

hist(cars$dist,
     main = "Car Distance",
     xlab = "Distance",
     col = "blue",
     freq = TRUE)

# 9. plot speed versus distance

plot(cars$speed,cars$dist,
       xlab="speed",
       ylab="distance")

# 10. add axis labels and a title to this plot

plot(cars$speed,cars$dist,
       xlab="speed",
       ylab="distance",
      main = "Speed vs. Distance"
     )

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