At Westonci.ca, we make it easy to get the answers you need from a community of informed and experienced contributors. Discover in-depth solutions to your questions from a wide range of experts on our user-friendly Q&A platform. Explore comprehensive solutions to your questions from knowledgeable professionals across various fields on our platform.
Sagot :
Sure! Let's break this down step-by-step using the empirical rule ([tex]$68\%-95\%-99.7\%$[/tex] rule) which applies to normal distributions.
### Step 1: Understand the Problem
- Mean ([tex]\(\mu\)[/tex]): 750 hours
- Standard Deviation ([tex]\(\sigma\)[/tex]): 75 hours
- Lower Bound: 525 hours
- Upper Bound: 750 hours
### Step 2: Convert Hours to Z-Scores
First, we'll convert the given hours into z-scores. The z-score for a value [tex]\(X\)[/tex] is calculated using the formula:
[tex]\[ z = \frac{X - \mu}{\sigma} \][/tex]
#### Calculate the z-score for the lower bound (525 hours):
[tex]\[ z_{\text{lower}} = \frac{525 - 750}{75} = -3.0 \][/tex]
#### Calculate the z-score for the upper bound (750 hours):
[tex]\[ z_{\text{upper}} = \frac{750 - 750}{75} = 0.0 \][/tex]
### Step 3: Determine the Probability from Z-Scores
Using the empirical rule:
- The empirical rule states that approximately 68% of the data lies within one standard deviation from the mean.
- Specifically, 34.13% of the data lies between the mean and one standard deviation below the mean ([tex]\( \mu - \sigma \)[/tex]).
- The total area under the normal curve is 1 (or 100%).
#### Find the probability corresponding to [tex]\( z = -3.0 \)[/tex]:
- By the empirical rule, the probability of a z-score of [tex]\(-1\)[/tex] to the left of the mean (which corresponds to 525 hours) is the remaining area in the left tail, which is:
[tex]\[ \text{Probability below z = -1} = 0.1587 \][/tex]
#### Find the probability corresponding to [tex]\( z = 0 \)[/tex]:
- A [tex]\( z \)[/tex]-score of 0 corresponds to the mean, and 50% of the data is below the mean because the mean splits the distribution exactly in half.
[tex]\[ \text{Probability below z = 0} = 0.5 \][/tex]
### Step 4: Calculate the Desired Probability
The probability that a light bulb lasts between 525 and 750 hours is the area under the normal curve between [tex]\( z = -3.0 \)[/tex] and [tex]\( z = 0 \)[/tex].
[tex]\[ \text{Probability (525 < b < 750)} = \text{Probability (b < 750)} - \text{Probability (b < 525)} \][/tex]
Substituting the corresponding probabilities:
[tex]\[ \text{Probability (525 < b < 750)} = 0.5 - 0.1587 = 0.3413 \][/tex]
### Conclusion
The probability that a given light bulb lasts between 525 and 750 hours is 0.3413, or 34.13%.
### Step 1: Understand the Problem
- Mean ([tex]\(\mu\)[/tex]): 750 hours
- Standard Deviation ([tex]\(\sigma\)[/tex]): 75 hours
- Lower Bound: 525 hours
- Upper Bound: 750 hours
### Step 2: Convert Hours to Z-Scores
First, we'll convert the given hours into z-scores. The z-score for a value [tex]\(X\)[/tex] is calculated using the formula:
[tex]\[ z = \frac{X - \mu}{\sigma} \][/tex]
#### Calculate the z-score for the lower bound (525 hours):
[tex]\[ z_{\text{lower}} = \frac{525 - 750}{75} = -3.0 \][/tex]
#### Calculate the z-score for the upper bound (750 hours):
[tex]\[ z_{\text{upper}} = \frac{750 - 750}{75} = 0.0 \][/tex]
### Step 3: Determine the Probability from Z-Scores
Using the empirical rule:
- The empirical rule states that approximately 68% of the data lies within one standard deviation from the mean.
- Specifically, 34.13% of the data lies between the mean and one standard deviation below the mean ([tex]\( \mu - \sigma \)[/tex]).
- The total area under the normal curve is 1 (or 100%).
#### Find the probability corresponding to [tex]\( z = -3.0 \)[/tex]:
- By the empirical rule, the probability of a z-score of [tex]\(-1\)[/tex] to the left of the mean (which corresponds to 525 hours) is the remaining area in the left tail, which is:
[tex]\[ \text{Probability below z = -1} = 0.1587 \][/tex]
#### Find the probability corresponding to [tex]\( z = 0 \)[/tex]:
- A [tex]\( z \)[/tex]-score of 0 corresponds to the mean, and 50% of the data is below the mean because the mean splits the distribution exactly in half.
[tex]\[ \text{Probability below z = 0} = 0.5 \][/tex]
### Step 4: Calculate the Desired Probability
The probability that a light bulb lasts between 525 and 750 hours is the area under the normal curve between [tex]\( z = -3.0 \)[/tex] and [tex]\( z = 0 \)[/tex].
[tex]\[ \text{Probability (525 < b < 750)} = \text{Probability (b < 750)} - \text{Probability (b < 525)} \][/tex]
Substituting the corresponding probabilities:
[tex]\[ \text{Probability (525 < b < 750)} = 0.5 - 0.1587 = 0.3413 \][/tex]
### Conclusion
The probability that a given light bulb lasts between 525 and 750 hours is 0.3413, or 34.13%.
We hope you found this helpful. Feel free to come back anytime for more accurate answers and updated information. Thank you for choosing our platform. We're dedicated to providing the best answers for all your questions. Visit us again. Get the answers you need at Westonci.ca. Stay informed with our latest expert advice.