Outcomes are very important when we want to know how likely things are to happen in an experiment. Let’s break down the key ideas:

1. Sample Space: This is just a fancy term for all the possible outcomes in an experiment.

   For example, when you flip a coin, there are two possible outcomes: heads or tails. We write this as the sample space: {H, T} where H means heads and T means tails.

2. Events: An event is just one specific outcome or a group of outcomes.

   So, if you want to focus on getting heads when flipping a coin, that's an event.

3. Calculating Probability: To find the probability of an event happening, we can use this simple formula:

   $P(Event) = \frac{Number \ of \ favorable \ outcomes}{Total \ number \ of \ outcomes}$

   Basically, you look at how many ways the event can happen (favorable outcomes) and divide that by the total number of outcomes.

When we understand how outcomes and events work together, it helps us better predict how likely something is to happen. This makes understanding statistics much easier!