To estimate the probability of getting a green pea, we use the empirical probability formula:

$P(\text{green pea}) = \frac{\text{Number of green peas}}{\text{Total number of peas}}$

Given:

• Number of green peas = 366
• Number of yellow peas = 533
• Total number of peas = $366 + 533 = 899$

Step 1: Calculate the empirical probability

$P(\text{green pea}) = \frac{366}{899} \approx 0.407$

So, the probability of getting a green pea is approximately 0.407.

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Step 2: Compare with the expected value $\frac{3}{4} = 0.75$

Clearly, the result $0.407$ is not very close to the expected value of 0.75. This suggests that either there might be some experimental deviation, or the underlying assumptions about the expected proportion may not hold.

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Do you need further clarification on how these probabilities work or any other details?

Here are 5 related questions to consider:

1. How can we interpret probabilities using relative frequency in the long term?
2. What statistical tests can determine if the observed ratio significantly differs from the expected ratio?
3. What could be some reasons for deviation from expected genetic outcomes?
4. How would the probability change if the sample size was larger?
5. How is a chi-square test used to compare observed and expected outcomes in genetics?

Tip: When comparing observed and expected outcomes, increasing the sample size tends to reduce random deviations.