3 A play is enjoying a long run at a theatre. It is found that the play time may be modelled as a normal variable with mean 130 minutes and standard deviation 3 minutes, and that the length of the intermission in the middle of the performance may be modelled by a normal variable with mean 15 minutes and standard deviaton 5 minutes. Find the probability that the performance is completed in less than 140 minutes.
3 A play is enjoying a long run at a theatre. It is found that the play time may be modelled as a normal variable with mean 130 minutes and standard deviation 3 minutes, and that the length of the intermission in the middle of the performance may be modelled by a normal variable with mean 15 minutes and standard deviaton 5 minutes. Find the probability that the performance is completed in less than 140 minutes.
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![### Probability Calculation of Play Completion Time
Consider a play that is being performed regularly at a local theatre. The duration of the play and its intermission can both be described using normal distributions.
#### Given Data:
1. **Play Time:**
- Mean (\(\mu_{\text{play}}\)): 130 minutes
- Standard Deviation (\(\sigma_{\text{play}}\)): 3 minutes
2. **Intermission Time:**
- Mean (\(\mu_{\text{intermission}}\)): 15 minutes
- Standard Deviation (\(\sigma_{\text{intermission}}\)): 5 minutes
We aim to find the probability that the total performance (play plus intermission) is completed within 140 minutes.
### Aggregated Distribution of Performance Time
Define:
- \(X\): Random variable representing the play time
- \(Y\): Random variable representing the intermission time
These variables are independently normally distributed:
- \(X \sim N(130, 3^2)\)
- \(Y \sim N(15, 5^2)\)
The total performance time \(Z\) is the sum of \(X\) and \(Y\):
\[ Z = X + Y \]
The mean (\(\mu_Z\)) and variance (\( \sigma_Z^2 \)) of \(Z\) are given by:
\[ \mu_Z = \mu_{\text{play}} + \mu_{\text{intermission}} = 130 + 15 = 145 \]
\[ \sigma_Z^2 = \sigma_{\text{play}}^2 + \sigma_{\text{intermission}}^2 = 3^2 + 5^2 = 9 + 25 = 34 \]
\[ \sigma_Z = \sqrt{34} \]
Thus, \(Z\) follows a normal distribution:
\[ Z \sim N(145, \sqrt{34}) \]
### Probability Calculation
We need to calculate:
\[ P(Z < 140) \]
### Standardizing the Normal Variable
Convert \(Z\) to the standard normal variable \(Z'\):
\[ Z' = \frac{Z - \mu_Z}{\sigma_Z} = \frac{140 - 145}{\sqrt{34}} = \frac{140 - 145}{5.831} = -0.857 \]
### Using the Standard Normal Distribution Table
Determine the probability corresponding to](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F732159e0-135e-441a-8a8d-d8e4bb926137%2Facadab93-7d30-4d7a-b4c0-666a5410f324%2Fu6nxgvb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Probability Calculation of Play Completion Time
Consider a play that is being performed regularly at a local theatre. The duration of the play and its intermission can both be described using normal distributions.
#### Given Data:
1. **Play Time:**
- Mean (\(\mu_{\text{play}}\)): 130 minutes
- Standard Deviation (\(\sigma_{\text{play}}\)): 3 minutes
2. **Intermission Time:**
- Mean (\(\mu_{\text{intermission}}\)): 15 minutes
- Standard Deviation (\(\sigma_{\text{intermission}}\)): 5 minutes
We aim to find the probability that the total performance (play plus intermission) is completed within 140 minutes.
### Aggregated Distribution of Performance Time
Define:
- \(X\): Random variable representing the play time
- \(Y\): Random variable representing the intermission time
These variables are independently normally distributed:
- \(X \sim N(130, 3^2)\)
- \(Y \sim N(15, 5^2)\)
The total performance time \(Z\) is the sum of \(X\) and \(Y\):
\[ Z = X + Y \]
The mean (\(\mu_Z\)) and variance (\( \sigma_Z^2 \)) of \(Z\) are given by:
\[ \mu_Z = \mu_{\text{play}} + \mu_{\text{intermission}} = 130 + 15 = 145 \]
\[ \sigma_Z^2 = \sigma_{\text{play}}^2 + \sigma_{\text{intermission}}^2 = 3^2 + 5^2 = 9 + 25 = 34 \]
\[ \sigma_Z = \sqrt{34} \]
Thus, \(Z\) follows a normal distribution:
\[ Z \sim N(145, \sqrt{34}) \]
### Probability Calculation
We need to calculate:
\[ P(Z < 140) \]
### Standardizing the Normal Variable
Convert \(Z\) to the standard normal variable \(Z'\):
\[ Z' = \frac{Z - \mu_Z}{\sigma_Z} = \frac{140 - 145}{\sqrt{34}} = \frac{140 - 145}{5.831} = -0.857 \]
### Using the Standard Normal Distribution Table
Determine the probability corresponding to
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