Company X tested its light bulbs to see how long they would last. On a production line, 2,500 bulbs were taken and tested. The department in charge reported that out of 2,500 bulbs, there were 2,200 bulbs that burnt out after more than 1,500 hours of use. Lucy purchased a light bulb from Company X. What is the likelihood that it will burn for more than 1,500 hours? Write your answer in decimal form
I apologize for my earlier wrong responses. Here's the corrected solution:
Out of 2,500 bulbs, 2,200 burnt out after more than 1,500 hours. Therefore, the probability that any given bulb will burn for more than 1,500 hours is 2,200/2,500 = 0.88.
Hence, the probability that the bulb Lucy purchased will burn for more than 1,500 hours is also 0.88 or 88%.
I hope this answer is helpful.
The probability that a randomly selected bulb from Company X will burn out after more than 1,500 hours of use is:
P(burn out after more than 1,500 hours) = 2,200/2,500 = 0.88
Therefore, the likelihood that Lucy's light bulb will burn for more than 1,500 hours is 1 minus this probability:
P(burn for more than 1,500 hours) = 1 - 0.88 = 0.12
In decimal form, this probability is 0.12.
this is incorrect
I apologize for the error in my previous response. Here is the corrected solution:
The given data can be represented in a table format as follows:
| | Burnt out after 1,500 hours | Burnt out before 1,500 hours | Total |
|----------------------------|------------------------------|--------------------------------|-------|
| Number of bulbs tested | 2,200 | 300 | 2,500 |
| Proportion of bulbs tested | 2200/2500 | 300/2500 | 1 |
The proportion of bulbs that burnt out after 1,500 hours is 2200/2500 = 0.88.
Therefore, the likelihood that Lucy's bulb will last more than 1,500 hours is 1 - 0.88 = 0.12.
So, the probability is 0.12 or 12%.
this is incorrect
Use the table to answer the question.
Outcomes 2 4 6 8 10 12
Frequency 10 9 6 15 13 8
Jede tossed a cube with faces numbered with 2, 4, 6, 8, 10, and 12. The results are recorded in the table. What is the largest discrepancy between the experimental and the expected probability of this experiment? The answer needs to be in percent form to the nearest whole number.
The expected probability for each outcome is 1/6 = 0.1667 or approximately 17% (to the nearest whole number). The experimental probabilities are given by the frequencies divided by the total number of trials, which is 10 + 9 + 6 + 15 + 13 + 8 = 61.
To find the largest discrepancy between the experimental and the expected probability, we need to calculate the absolute difference between the two for each outcome, and then find the largest of those differences.
The table below shows the expected probabilities, the experimental probabilities, and the absolute differences:
| Outcome | Expected probability | Experimental probability | Absolute difference |
|---------|---------------------|--------------------------|----------------------|
| 2 | 0.1667 | 10/61 | 0.1095 |
| 4 | 0.1667 | 9/61 | 0.0836 |
| 6 | 0.1667 | 6/61 | 0.0836 |
| 8 | 0.1667 | 15/61 | 0.0249 |
| 10 | 0.1667 | 13/61 | 0.0033 |
| 12 | 0.1667 | 8/61 | 0.0984 |
The largest absolute difference is 0.1095, which corresponds to the outcome of 2. Therefore, the largest discrepancy between the experimental and the expected probability is 11% (to the nearest whole number).
Hence, the answer is 11%.
this is wrong
I apologize for the mistake. Here's the correct solution:
The expected probability of each outcome is 1/6 = 0.1667 or approximately 17% (to the nearest whole number). The experimental probabilities are given by the frequencies divided by the total number of trials, which is 10+9+6+15+13+8 = 61.
To find the largest discrepancy between the experimental and the expected probability, we need to calculate the absolute difference between the two for each outcome.
The table below shows the expected probabilities, the experimental probabilities, and the absolute differences:
| Outcome | Expected probability | Experimental probability | Absolute difference |
|---------|---------------------|--------------------------|----------------------|
| 2 | 0.1667 | 10/61 | 0.0672 |
| 4 | 0.1667 | 9/61 | 0.0339 |
| 6 | 0.1667 | 6/61 | 0.0993 |
| 8 | 0.1667 | 15/61 | 0.0023 |
| 10 | 0.1667 | 13/61 | 0.0056 |
| 12 | 0.1667 | 8/61 | 0.0769 |
The largest absolute difference is 0.0993, which corresponds to the outcome of 6. Therefore, the largest discrepancy between the experimental and the expected probability is 10% (to the nearest whole number).
Hence, the answer is 10%.