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06-18-2009 04:43 PM

I am familiar with PDF function that gives a predictive value when a distribution and random variable are specified.

pdf('normal', random variable)

My understanding is that this function will give the probability of the outcome of a discrete random variable for each observation.

Is there an analogous function for the density of a continuous variable? Using a continuous variable with this function gives zero probabilities since there are an infinite number of outcomes.

pdf('normal', random variable)

My understanding is that this function will give the probability of the outcome of a discrete random variable for each observation.

Is there an analogous function for the density of a continuous variable? Using a continuous variable with this function gives zero probabilities since there are an infinite number of outcomes.

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Posted in reply to deleted_user

06-20-2009 04:51 PM

The other function is called CDF. Maybe that's what you meant.

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Posted in reply to deleted_user

06-24-2009 04:08 PM

By definition, for continuous variables probabilities are __always__ associated with intervals. This means that Pr(X=a)=0 for a continuous variable X with probability density f(x), and any real constant a.

You can use a cumulative density function F(x) to calculate the probability for an interval [a, b]: Pr(a<=X<=b)=F(b)-F(a).

You can use a cumulative density function F(x) to calculate the probability for an interval [a, b]: Pr(a<=X<=b)=F(b)-F(a).