Probability is all about working out how likely something is...
Understanding Probability





Probability and the Probability Scale
Ever wondered why weather forecasts talk about "30% chance of rain"? That's probability in action - a way of measuring how likely something is to happen.
The probability scale runs from 0 to 1, where 0 means impossible and 1 means certain. You can write probabilities as fractions (like ½), decimals (like 0.5), or percentages (like 50%). Think of it like a sliding scale: picking a blue counter from a bag of only red counters sits at 0, whilst Monday following Sunday sits firmly at 1.
To calculate theoretical probability, use this simple formula: number of ways the outcome can happen ÷ total number of possible outcomes. For example, rolling a 4 on a dice gives you 1 ÷ 6 = ⅙, because there's one way to get a 4 out of six possible numbers.
Quick Check: Rolling an odd number on a dice? There are three odd numbers (1, 3, 5) out of six possible outcomes, so that's 3 ÷ 6 = ½!

Relative Frequency and Experimental Probability
Real life isn't always as neat as theory suggests. Relative frequency (also called experimental probability) shows what actually happens when you run experiments in the real world.
If you flip a coin 100 times, theory says you should get 50 heads. But you might actually get 59 heads and 41 tails, making your relative frequency 59/100 or 59%. This approach becomes essential when dealing with biased dice or unfair coins, where theoretical probability doesn't apply.
The more times you repeat an experiment, the more reliable your relative frequency becomes. It's like getting a clearer picture by adding more data points - 50 coin flips gives you a better estimate than just 10 flips.
Real-World Tip: Sports statistics use relative frequency all the time - a footballer's goal-scoring record is based on past performance, not theoretical calculations!

Combined Events and Systematic Approaches
When multiple events happen together, you need organised methods to avoid missing possibilities. Systematic listing helps you find all outcomes in a logical order.
Frequency trees organise information visually when you're given actual numbers rather than probabilities. For example, if a running club has 160 members with specific breakdowns by gender and age, you can map this out systematically to calculate probabilities for randomly selected members.
Tree diagrams show all possible outcomes when events happen in sequence. Each branch represents a possible outcome with its probability clearly marked. For independent events (like rolling dice twice), the outcome of the first event doesn't affect the second.
Memory Trick: With tree diagrams, multiply probabilities along branches to find the probability of that specific path happening.

Working with Tree Diagrams
Tree diagrams become powerful tools when you need to calculate probabilities for sequences of events. Each path through the tree represents one possible outcome.
To find the probability of any specific combination, simply multiply the probabilities along that branch. For instance, rolling two sixes in a row: ⅙ × ⅙ = 1/36.
The beauty of tree diagrams lies in their completeness - they show every possible outcome clearly. Whether you're looking at rolling dice, drawing cards, or any other sequential events, the visual layout helps you avoid missing crucial combinations.
Pro Tip: Always check that all your final probabilities add up to 1 - this confirms you haven't missed any outcomes or made calculation errors!
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Ever wondered why weather forecasts talk about "30% chance of rain"? That's probability in action - a way of measuring how likely something is to happen.
The probability scale runs from 0 to 1, where 0 means impossible and 1 means certain. You can write probabilities as fractions (like ½), decimals (like 0.5), or percentages (like 50%). Think of it like a sliding scale: picking a blue counter from a bag of only red counters sits at 0, whilst Monday following Sunday sits firmly at 1.
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Relative Frequency and Experimental Probability
Real life isn't always as neat as theory suggests. Relative frequency (also called experimental probability) shows what actually happens when you run experiments in the real world.
If you flip a coin 100 times, theory says you should get 50 heads. But you might actually get 59 heads and 41 tails, making your relative frequency 59/100 or 59%. This approach becomes essential when dealing with biased dice or unfair coins, where theoretical probability doesn't apply.
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