Understanding Joint Probability Density Functions | Examples and Key Concepts In this video, we examine joint probability density functions (PDFs), a key concept in probability and statistics that ...

Probability theory constitutes the mathematical framework for quantifying uncertainty and analysing random phenomena. Its foundations lie in measure theory, where a probability space is defined as a ...

Explain why probability is important to statistics and data science. See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance ...

Continuous Variable: can take on any value between two specified values. Obtained by measuring. Discrete Variable: not continuous variable (cannot take on any value between two specified values).