Answer: Technical sales engineer
Explanation:
An analysis engineer makes use of data and other technical information in order for him or her to be able to analyze a project plan, and provide necessary solutions.
Technical sales engineers gives their clients the needed support and sales advice for their business to thrive. Technical sales engineers helps their clients in giving technical advices, answering queries, as well as introducing new products.
Design engineers are the engineers that study, and develop ideas that will be used for new products. Sometimes, they also modify systems used in production so that organizational performance can be improved.
Inspection engineers are the engineers that looks at infrastructures and identify the problems affecting them e.g oil pipelines, roads, bridges, etc so that accidents will be prevented.
Consulting engineer is an engineer that deals with the planning, and infrastructures. Their work benefits the society as a whole.
Based on the above explanation, the answer is technical sales engineer.
Answer:
if I am not wrong the volumetric flow rate into the finance if the year inter 868 1.00 pm
Answer:
0.14% probability of observing more than 4 errors in the carpet
Explanation:
When we only have the mean, we use the Poisson distribution.
In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D)
In which
x is the number of sucesses
e = 2.71828 is the Euler number
is the mean in the given interval.
The number of weaving errors in a twenty-foot by ten-foot roll of carpet has a mean of 0.8.
This means that ![\mu = 0.8](https://tex.z-dn.net/?f=%5Cmu%20%3D%200.8)
What is the probability of observing more than 4 errors in the carpet
Either we observe 4 or less errors, or we observe more than 4. The sum of the probabilities of these outcomes is 1. So
![P(X \leq 4) + P(X > 4) = 1](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%2B%20P%28X%20%3E%204%29%20%3D%201)
We want P(X > 4). Then
![P(X > 4) = 1 - P(X \leq 4)](https://tex.z-dn.net/?f=P%28X%20%3E%204%29%20%3D%201%20-%20P%28X%20%5Cleq%204%29)
In which
![P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29%20%2B%20P%28X%20%3D%202%29%20%2B%20P%28X%20%3D%203%29%20%2B%20P%28X%20%3D%204%29)
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D)
![P(X = 0) = \frac{e^{-0.8}*(0.8)^{0}}{(0)!} = 0.4493](https://tex.z-dn.net/?f=P%28X%20%3D%200%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B0%7D%7D%7B%280%29%21%7D%20%3D%200.4493)
![P(X = 1) = \frac{e^{-0.8}*(0.8)^{1}}{(1)!} = 0.3595](https://tex.z-dn.net/?f=P%28X%20%3D%201%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B1%7D%7D%7B%281%29%21%7D%20%3D%200.3595)
![P(X = 2) = \frac{e^{-0.8}*(0.8)^{2}}{(2)!} = 0.1438](https://tex.z-dn.net/?f=P%28X%20%3D%202%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B2%7D%7D%7B%282%29%21%7D%20%3D%200.1438)
![P(X = 3) = \frac{e^{-0.8}*(0.8)^{3}}{(3)!} = 0.0383](https://tex.z-dn.net/?f=P%28X%20%3D%203%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B3%7D%7D%7B%283%29%21%7D%20%3D%200.0383)
![P(X = 4) = \frac{e^{-0.8}*(0.8)^{4}}{(4)!} = 0.0077](https://tex.z-dn.net/?f=P%28X%20%3D%204%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B4%7D%7D%7B%284%29%21%7D%20%3D%200.0077)
![P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.4493 + 0.3595 + 0.1438 + 0.0383 + 0.0077 = 0.9986](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29%20%2B%20P%28X%20%3D%202%29%20%2B%20P%28X%20%3D%203%29%20%2B%20P%28X%20%3D%204%29%20%3D%200.4493%20%2B%200.3595%20%2B%200.1438%20%2B%200.0383%20%2B%200.0077%20%3D%200.9986)
![P(X > 4) = 1 - P(X \leq 4) = 1 - 0.9986 = 0.0014](https://tex.z-dn.net/?f=P%28X%20%3E%204%29%20%3D%201%20-%20P%28X%20%5Cleq%204%29%20%3D%201%20-%200.9986%20%3D%200.0014)
0.14% probability of observing more than 4 errors in the carpet
Answer:
Q = 125.538 W
Explanation:
Given data:
D = 30 cm
Temperature
degree celcius
![T_S = 220 + 273 = 473 K](https://tex.z-dn.net/?f=T_S%20%3D%20%20220%20%2B%20273%20%3D%20473%20K)
Heat coefficient = 12 W/m^2 K
Efficiency 80% = 0.8
![Q = hA(T_S - T_{\infty}) \eta](https://tex.z-dn.net/?f=Q%20%3D%20hA%28T_S%20-%20T_%7B%5Cinfty%7D%29%20%5Ceta)
![= 12(\frac{\pi}{4} 0.3^2) (473 - 288) 0.8](https://tex.z-dn.net/?f=%3D%2012%28%5Cfrac%7B%5Cpi%7D%7B4%7D%200.3%5E2%29%20%28473%20-%20288%29%200.8)
Q = 125.538 W