The thrill of riding a roller coaster is addictive, both for its users who take the ride, and for the designers and engineers
to make them bigger and faster. On the internet, there are many data sets available that rank popular roller coasters according to their maximum speed, the g-force experienced, or the height, to allow you maximizing your thrill. In this case study, we will investigate one of these data sets, counting 408 roller coasters, half of them in North America, and the others in Latin America and Europe. Important variables in the data set that affect the thrill are Height (in meters), Speed (in miles per hours, mph), Length (in meters), and Duration (in seconds). But connoisseurs will also be interested in knowing if the coaster is of steel or wood (Type or also Construction), if there are any Inversions (Yes/No) and if so, how many (Numinversions), the maximum g-force (GForce) or when it was constructed (Opened). As with all real data sets, the data are incomplete: for quite a lot of coasters, we are missing values for one or several of the variables. We will perform all our analyses on the largest possible data set, excluding only those records that contain missing values for the specific analysis.
What variables in our data set are of quantitative type? Select all that apply.
A.
Speed
B.
Country
C.
Inversions
D.
GForce
E.
Height
F.
Opened
G.
Duration
H.
Numinversions
I.
Type
J.
Length
