Intro

hist(mtcars$mpg)

1. Cars with mpg of betweeen 15 and 20 are the most common, with the frequency of such an occurrence in the dataset being 12 times. The data is right-skewed.
summary(mtcars$mpg)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.40   15.43   19.20   20.09   22.80   33.90
2. The range of the cars’ mpg is from approx. 10 to 34. We can see the skewness from observing the 1st and 3rd quartiles, with the distance from the 3rd quartile to the max being significant. The mean of 20.09 is greater than the median of 19.2, also pointing to some skewness being present.
plot(mtcars$mpg, mtcars$disp)

boxplot(mtcars$mpg~mtcars$cyl, data=mtcars)

boxplot(mtcars$mpg~mtcars$vs, data=mtcars)

boxplot(mtcars$mpg~mtcars$am, data=mtcars)

boxplot(mtcars$mpg~mtcars$gear, data=mtcars)

3. From the first plot, we gather that, on average, as car disp decreases, car mpg will increase. From the first boxplot, we gather that car mpg is highest with 4 cyl cars, with a steady decrease of mpg with 6 cyl, and then some more with 8 cyl. From the second and third boxplots, we gather that cars with more mpg have higher vs and am on average than cars with less mpg. From the final boxplot, we gather that cars with 3 gears have less mpg (with a much lesser min) on average than those with 4 and 5 gears, the two of whom look fairly similar.
mean(mtcars$mpg)
## [1] 20.09062
avgmpg <- mean(mtcars$mpg)
isHigh <- mtcars[(mtcars$mpg<avgmpg),]
isLow <- mtcars[(mtcars$mpg>=avgmpg),]
rbind(isLow,isHigh)
##                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
## Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
## Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
## Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
## Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
## Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
## Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
## Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
## Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
## Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
## Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
## Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
## Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
## Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
## Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
## Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
## Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
## Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
## Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
## Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
## Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
## Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
## Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
## AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
## Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
## Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
## Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
## Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
## Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
4. Through finding the average mpg and then using the logical expression brackets, we are able to create the categories and bind them to form a chart displaying the cars with above average mpg (20.09 mpg) grouped at the top.
boxplot(iris$Petal.Length~iris$Species, data=iris)

5. From the boxplots, we find that the iris species Setosa very visibly contains smaller petal length when compared with the two other iris species. It’s species will be the easiest to distinguish if strictly going by petal length. While there is a tiny bit of overlap between iris species versicolor and virginica’s petal lengths, virginica has the longer petal lengths most of the time, which is evident due to virginica having a noticeably higher median, mean, and max range.