stat 390 - continuous random variable distribution

(T/F) cdfs are the derivatives of pdfs

F - they are the antiderivatives

(T/F) pdfs are the derivatives of cdfs

T - they are the derivatives

probability density function (pdf)

a graph / equation representing probabilities for a continuous random variable

cumulative distribution function (cdf)

a graph / equation representing the sum of probabilities for a continuous random variable

how to find cdf from pdf

integrate pdf

how to find pdf from cdf

derive cdf

expectation of a continuous random variable (E[X])

= ∫ x*f(x)dx
- bounds typically given