Random Vectors with Different Units
Define a joint height‐weight distribution with assumed correlation of 0.65.
In[1]:=
hw\[ScriptCapitalD] =
BinormalDistribution[{Quantity[1.8, "Meters"],
Quantity[85, "Kilograms"]}, {Quantity[0.15, "Meters"],
Quantity[9, "Kilograms"]}, 0.65]Out[1]=
Compute the probability of a person's height being over 1.75 meters, given that the person's weight is above 72 kilograms.
In[2]:=
NProbability[
h > Quantity[1.75, "m"] \[Conditioned]
w > Quantity[72, "kg"], {h, w} \[Distributed] hw\[ScriptCapitalD]]Out[2]=
Compute the distribution of the body mass index (BMI) for the assumed population.
In[3]:=
bmi\[ScriptCapitalD] =
TransformedDistribution[
w/h^2, {h, w} \[Distributed] hw\[ScriptCapitalD]]Out[3]=
Estimate the distribution of the BMI using a sample histogram.
In[4]:=
sample = RandomVariate[bmi\[ScriptCapitalD], 10^5];
Histogram[sample, Automatic, "PDF", AxesLabel -> Automatic]Out[4]=
