To determine the truth of the statements regarding the experimental probability of being right-handed based on the survey results, we first need to calculate the experimental probability.
- Total participants in the survey: 300
- Number of right-handed participants: 270
- Number of left-handed participants: 30
The experimental probability (P) of being right-handed is calculated as: \[ P(\text{right-handed}) = \frac{\text{Number of right-handed participants}}{\text{Total number of participants}} = \frac{270}{300} = 0.9 \]
The theoretical probability of being right-handed varies by population data, but generally, it’s often cited that approximately 90% of the population is right-handed. This means that for many populations, the theoretical probability (T) of being right-handed can be assumed to be around 0.9 or 90%.
Let’s analyze the statements:
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The experimental probability that a person is right-handed is greater than the theoretical probability. This could be true if we assume the theoretical probability is around 0.9, making this statement false as the experimental is equal to 0.9.
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The experimental probability that a person is right-handed is 50. This is false as the experimental probability is 0.9 or 90%, not 50%.
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The experimental probability that a person is right-handed is less than the theoretical probability. This is false since both values are 0.9, meaning they are equal.
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The experimental probability that a person is right-handed is equal to the theoretical probability. This statement is true if we assume the theoretical probability is also around 0.9.
Therefore, the correct statement is: The experimental probability that a person is right-handed is equal to the theoretical probability.