Data Handling - Language of Probability

Understanding Probability: Probability is the study of how likely an event is to happen. We use specific words to describe these chances, ranging from things that can never happen to things that will definitely happen. Imagine a 'Probability Line' where the far left is 'Impossible' and the far right is 'Certain'.

Impossible Events: An event is impossible if it has a $0$ chance of occurring. For example, rolling a $7$ on a standard $6$-sided die or seeing a real cow fly over the moon. On a visual scale, this is the very beginning of the line.

Certain Events: An event is certain if it is $100\%$ guaranteed to happen. For example, the sun rising in the morning or picking a red bead from a box that only contains red beads. This sits at the very end of our probability line.

Unlikely and Likely: These terms describe events that might happen but aren't guaranteed. 'Unlikely' means there is a small chance (like picking a green marble from a bag of $10$ marbles where only $1$ is green). 'Likely' means there is a high chance (like picking a green marble if $9$ out of $10$ are green).

Even Chance: This happens when an event is just as likely to occur as it is not to occur. It is a $50/50$ chance. A classic visual is a coin toss, where landing on 'Heads' is just as likely as landing on 'Tails'. On the probability scale, this is exactly in the middle.

Outcomes and Sample Space: An 'outcome' is a single result of an experiment, like getting a '4' on a die. The 'sample space' is a list of all possible outcomes. For a spinner with three colors (Red, Blue, Yellow), the sample space is $\{Red, Blue, Yellow\}$.

Fair vs. Unfair: In probability, a game or tool is 'fair' if every outcome has an equal chance. For example, a spinner divided into $4$ equal-sized quarters is fair. If one color takes up half the circle and the others are tiny, the spinner is 'unfair' or biased.