Lecture 11 is great, very interesting, however I have a question regarding the definition of the BinomialRandomVariable class- specifically: why does it include the DiscreteRandomVariable class in its parameters?
I ask because it seemed odd to me to include it; and I may be mistaken, but removing the (DiscreteRandomVariable ) parameter from the BinomialRandomVariable class definition appears to have no impact on the function or outcome of the code?
I'm probably making an error that I just can't see but would love to have this cleared up - thank you fellow Quantopians!!
class BinomialRandomVariable(DiscreteRandomVariable):
def __init__(self, numberOfTrials = 10, probabilityOfSuccess = 0.5):
self.variableType = "Binomial"
self.numberOfTrials = numberOfTrials
self.probabilityOfSuccess = probabilityOfSuccess
return
def draw(self, numberOfSamples):
samples = np.random.binomial(self.numberOfTrials, self.probabilityOfSuccess, numberOfSamples)
return samples vs.
class BinomialRandomVariable:
def __init__(self, numberOfTrials = 10, probabilityOfSuccess = 0.5):
self.variableType = "Binomial"
self.numberOfTrials = numberOfTrials
self.probabilityOfSuccess = probabilityOfSuccess
return
def draw(self, numberOfSamples):
samples = np.random.binomial(self.numberOfTrials, self.probabilityOfSuccess, numberOfSamples)
return samples 