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alina1380 [7]
3 years ago
15

A physicist working in a large laboratory has found that light particles traveling in a particle accelerator increase velocity i

n a manner that can be described by the linear function −4x + 3y = 21, where x is time and y is velocity in kilometers per hour. Use this function to determine when a certain particle will reach 30km/hr.
Mathematics
1 answer:
frutty [35]3 years ago
4 0

Answer:

17\ \text{hours and}\ 15\text{ minutes}

Step-by-step explanation:

The function is

-4x+3y=21

Where

x = Time in hours

y = Velocity in kilometers per hour

Here y = 30 km/hr

-4x+3y=21\\\Rightarrow x=\dfrac{3y-21}{4}\\\Rightarrow x=\dfrac{3\times 30-21}{4}\\\Rightarrow x=\dfrac{69}{4}\\\Rightarrow x=17.25\ \text{hours}=17\ \text{hours and}\ 15\text{ minutes}

The particle will reach 30 km/hr after 17\ \text{hours and}\ 15\text{ minutes}.

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nikitadnepr [17]

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Area: ½ × base × height

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Step-by-step explanation:

4 0
3 years ago
Assume that BK Call Center receives 2 phone calls in one hour on average. If the department works 10 hours a day receiving the c
MrMuchimi

Using the Poisson distribution, the probabilities are given as follows:

A. 0.0888 = 8.88%.

B. 0.1354 = 13.54%.

C. 0.8646 = 86.46%.

<h3>What is the Poisson distribution?</h3>

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by:

P(X = x) = \frac{e^{-\mu}\mu^{x}}{(x)!}

The parameters are:

  • x is the number of successes
  • e = 2.71828 is the Euler number
  • \mu is the mean in the given interval.

Item a:

10 hours, 2 calls per hour, hence the mean is given by:

\mu = 2 \times 10 = 20.

The probability is P(X = 20), hence:

P(X = x) = \frac{e^{-\mu}\mu^{x}}{(x)!}

P(X = 20) = \frac{e^{-20}20^{20}}{(20)!} = 0.0888

Item b:

1 hour, hence the mean is given by:

\mu = 2

The probability is P(X = 0), hence:

P(X = x) = \frac{e^{-\mu}\mu^{x}}{(x)!}

P(X = 0) = \frac{e^{-2}2^{0}}{(0)!} = 0.1354

Item c:

The probability is:

P(X \geq 1) = 1 - P(X = 0) = 1 - 0.1354 = 0.8646

More can be learned about the Poisson distribution at brainly.com/question/13971530

#SPJ1

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2 years ago
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