When we look at probability distributions, there are some interesting differences between discrete and continuous types:

• Nature of Values:

  • Discrete: This type deals with clear, separate values. Imagine rolling a die or counting how many students are in a class—these numbers are always whole numbers.
  • Continuous: This type can take any number within a certain range. For example, measuring height or time can include fractions or decimals.

• Probability Representation:

  • Discrete: Here, we find the probability for each specific outcome.
  • Continuous: In this case, we use something called probability density functions (PDFs). This means we often look at probabilities over a range instead of just one point.

So, it all comes down to the difference between counting and measuring!