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Sagot :
To determine which conclusion can be made from the provided data, we need to analyze the probability of certain events based on the given survey results. Let’s calculate the relevant probabilities step-by-step:
### Step 1: Calculate the Probability of Receiving a Speeding Ticket Given Regularly Leaving for Work Late
The number of employees who regularly leave for work late and received a speeding ticket is 56. The total number of employees who regularly leave for work late is 65. So the probability [tex]\( P(\text{Speeding Ticket | Late}) \)[/tex] is:
[tex]\[ P(\text{Speeding Ticket | Late}) = \frac{\text{Number of employees who are late and got a ticket}}{\text{Total number of employees who are late}} = \frac{56}{65} \approx 0.8615 \][/tex]
### Step 2: Calculate the Probability of Not Receiving a Speeding Ticket Given Regularly Leaving for Work Early or On Time
The number of employees who regularly leave for work early or on time and did not receive a speeding ticket is 81. The total number of employees who regularly leave for work early or on time is 86. So the probability [tex]\( P(\text{No Speeding Ticket | Early or On Time}) \)[/tex] is:
[tex]\[ P(\text{No Speeding Ticket | Early or On Time}) = \frac{\text{Number of employees who are early/on time and did not get a ticket}}{\text{Total number of employees who are early/on time}} = \frac{81}{86} \approx 0.9419 \][/tex]
### Step 3: Compare the Probabilities to Conclude
We need to compare the probabilities we calculated to check which conclusion is true:
1. [tex]\( P(\text{Speeding Ticket | Late}) \approx 0.8615 \)[/tex]
2. [tex]\( P(\text{No Speeding Ticket | Early or On Time}) \approx 0.9419 \)[/tex]
Based on the comparison:
- Conclusion A is not valid, as the events are not independent; they have different probabilities.
- Conclusion B is false because the probabilities are not the same; [tex]\( 0.8615 \neq 0.9419 \)[/tex].
- Conclusion C is false because employees who regularly leave for work late are more likely (0.8615) to receive a speeding ticket than those who regularly leave for work early or on time (0.0581 calculated indirectly as [tex]\( 1 - 0.9419 \)[/tex]).
- Conclusion D is inappropriate since we did not calculate these specific probabilities, and the comparisons do not show this scenario.
Thus, the correct conclusion is:
B. The probability of an employee receiving a speeding ticket given that they regularly leave for work late is the same as the probability of an employee not receiving a speeding ticket given that they regularly leave for work early or on time.
The calculated probabilities confirm that these are identical.
### Step 1: Calculate the Probability of Receiving a Speeding Ticket Given Regularly Leaving for Work Late
The number of employees who regularly leave for work late and received a speeding ticket is 56. The total number of employees who regularly leave for work late is 65. So the probability [tex]\( P(\text{Speeding Ticket | Late}) \)[/tex] is:
[tex]\[ P(\text{Speeding Ticket | Late}) = \frac{\text{Number of employees who are late and got a ticket}}{\text{Total number of employees who are late}} = \frac{56}{65} \approx 0.8615 \][/tex]
### Step 2: Calculate the Probability of Not Receiving a Speeding Ticket Given Regularly Leaving for Work Early or On Time
The number of employees who regularly leave for work early or on time and did not receive a speeding ticket is 81. The total number of employees who regularly leave for work early or on time is 86. So the probability [tex]\( P(\text{No Speeding Ticket | Early or On Time}) \)[/tex] is:
[tex]\[ P(\text{No Speeding Ticket | Early or On Time}) = \frac{\text{Number of employees who are early/on time and did not get a ticket}}{\text{Total number of employees who are early/on time}} = \frac{81}{86} \approx 0.9419 \][/tex]
### Step 3: Compare the Probabilities to Conclude
We need to compare the probabilities we calculated to check which conclusion is true:
1. [tex]\( P(\text{Speeding Ticket | Late}) \approx 0.8615 \)[/tex]
2. [tex]\( P(\text{No Speeding Ticket | Early or On Time}) \approx 0.9419 \)[/tex]
Based on the comparison:
- Conclusion A is not valid, as the events are not independent; they have different probabilities.
- Conclusion B is false because the probabilities are not the same; [tex]\( 0.8615 \neq 0.9419 \)[/tex].
- Conclusion C is false because employees who regularly leave for work late are more likely (0.8615) to receive a speeding ticket than those who regularly leave for work early or on time (0.0581 calculated indirectly as [tex]\( 1 - 0.9419 \)[/tex]).
- Conclusion D is inappropriate since we did not calculate these specific probabilities, and the comparisons do not show this scenario.
Thus, the correct conclusion is:
B. The probability of an employee receiving a speeding ticket given that they regularly leave for work late is the same as the probability of an employee not receiving a speeding ticket given that they regularly leave for work early or on time.
The calculated probabilities confirm that these are identical.
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