Statistics

Guiding Question: How can frequency support communication?

frequency vs. relative frequency

Frequency: This is simply the "count." It tells you how many times something happened.
- - Example: You flip a coin 10 times and get 6 heads. The frequency of heads is 6.
Relative Frequency: This is the "part-to-whole" comparison. It tells you how often something happened compared to the total number of trials.

The Three Forms: You can write relative frequency in three ways:
- - As a Fraction: 6/10
  - As a Decimal: 0.6
  - As a Percentage: 60%

Equally Likely: This means every possible outcome has the exact same chance of happening.
- - Examples: Flipping a fair coin (50/50), rolling a 6-sided die (1/6 for each number), or spinning a spinner with equal-sized colored sections.
What is an "Event"?: An event is a specific result you are looking for.
- - It could be one outcome (rolling a 4).
  - It could be a group of outcomes (rolling an even number: 2, 4, or 6).

The Big Idea: If you only flip a coin 4 times, you might get 4 heads (100%). That doesn't mean coins always land on heads!
The Law: The more times you perform an experiment (the "trials"), the closer your Relative Frequency will get to the actual Expected Likelihood.
Conclusion: Large amounts of data provide a much better estimate of what is actually likely to happen.

Identify Outcomes: List everything that could happen (e.g., on a spinner: Red, Blue, Green).
Collect Data: Run the experiment and record the frequency (the count) for each category.
Calculate Relative Frequency: Divide the count by the total number of times you ran the experiment.
Predict: Use your relative frequency to guess what might happen if you ran the experiment 1,000 more times.
Compare: Look at data from a small sample (10 trials) vs. a large sample (100 trials) to see how the relative frequency changes and becomes more stable.

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