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Interpretation: The relative frequency approximates the probability of landing on red in a
larger number of spins.
(learn to interpret these questions before trying to solve them, as you cannot solve a
question you don't fully understand)
2. Calculating Expected Frequencies
Expected Frequency: The predicted number of times an event will occur in a certain
number of trials based on its probability.
Formula:
Example:
If the probability of landing on blue in a spinner is P(Blue) = 0.4 and you spin the spinner
100 times:
Expected Frequency of Blue = 100×0.4 = 40
This means you expect to land on blue approximately 40 times.
3. Understanding Key Concepts
Fair: An experiment or device is fair if all outcomes have an equal probability.
Example: A fair six-sided die has a 1/6 chance for each number.
Bias: When an experiment or device consistently favors certain outcomes over others,
leading to inaccurate probabilities.
Example: A biased die that has a higher chance of landing on 6.
Random: Events that occur without any predictable pattern or influence, ensuring that each
outcome has a fair chance.
Example: Flipping a coin is random if it has no bias.
Summary
Relative Frequency provides an empirical estimate of probability based on actual results.
Expected Frequency is a theoretical prediction based on known probabilities.
Understanding fairness, bias, and randomness is crucial for interpreting results accurately.