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