NSDC Data Science Flashcards – Probability #3 – Cumulative Distribution Function

This NSDC Data Science Flashcards series will teach you about probability, including random variables, probability density functions, cumulative distribution functions, and expected values. This installment of the NSDC Data Science Flashcards series was created and recorded by Stephanie Guo. You can find these videos on the NEBDHub Youtube channel.

Hello everyone, my name is Stephanie and I am the Program Manager for the National Student Data Corps. Welcome to the NSDC Data Science Flashcard Video Series. This series will break down data science topics in simple terms that you can leverage throughout your data science journey. Today, we’ll be talking about probability.

Next up, the Cumulative Distribution Function, or CDF. This powerful function tells us the probability that a random variable is less than or equal to a particular value.

For discrete random variables, the CDF jumps up in steps. Each step represents a distinct value of the random variable.

For continuous random variables, the CDF is a smooth curve, indicating that the variable can take any value in a given range.

Understanding CDFs is essential for various statistical analyses and hypothesis testing.

Please follow along with the rest of the NSDC Data Science Flashcard series to learn more about math and probability.