To develop a probability model based on the observed frequencies, we need to calculate the probability of each letter by dividing the frequency of each letter by the total number of trials (100 in this case).
The frequencies given are:
- C: 20
- A: 25
- R: 30
- E: 10
- S: 15
Now, we calculate the probabilities:
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Probability of C (P(C)): \[ P(C) = \frac{20}{100} = 0.20 \]
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Probability of A (P(A)): \[ P(A) = \frac{25}{100} = 0.25 \]
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Probability of R (P(R)): \[ P(R) = \frac{30}{100} = 0.30 \]
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Probability of E (P(E)): \[ P(E) = \frac{10}{100} = 0.10 \]
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Probability of S (P(S)): \[ P(S) = \frac{15}{100} = 0.15 \]
Now, we can put these probabilities into a table format:
| X | C | A | R | E | S | |----|-----|-----|-----|-----|-----| | P(X) | 0.20 | 0.25 | 0.30 | 0.10 | 0.15 |
This gives us the probability model based on Jorelle's observations, rounded to the nearest hundredth.
Therefore, the correct response that matches this probability model is: \[ \text{X C A R E S P(X) } 0.20, 0.25, 0.30, 0.10, 0.15 \]