Data Science and Machine Learning (Theory and Projects) A to Z - Continuous Random Variables: Probability Density Functi

The video tutorial explains the properties of a valid probability density function (PDF) for a random variable X. It highlights that a PDF is always nonnegative and can exceed a value of one. The area under the PDF curve must equal one, which is the normalization condition. The video also clarifies that the random variable X can take any value, positive or negative, as long as the PDF remains nonnegative and the total area under the curve is one.

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