Probability distributions can be divided into two main types: discrete and continuous. They are different in how they show data.

1. What They Mean:

   • Discrete Distributions: These are used for results that you can count. For example, when you roll a die, the possible outcomes are just 1, 2, 3, 4, 5, or 6. You can count these results.
   • Continuous Distributions: These are used for results that you can measure. Think about measuring someone's height. It can be any number within a range, like 170.5 cm.

2. Examples:

   • Binomial Distribution: This is a discrete distribution. It looks at a set number of attempts. For example, you might count how many times you get heads when flipping a coin 10 times.
   • Normal Distribution: This is a continuous distribution. It often helps us understand real-life measurements, such as test scores. It is usually shown as a bell curve.

In short, the main difference between these two types of distributions is how the outcomes are handled. Discrete distributions deal with countable results, while continuous distributions deal with measurable results.