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aleksley [76]
3 years ago
12

Solve 3.4 [ 6 ( 4) +6^2] Please show your work! <3

Mathematics
1 answer:
VARVARA [1.3K]3 years ago
7 0

Answer:

204

Step-by-step explanation:

3.4[6(4)+6^2]=

3.4[24+36]=

3.4[60]=

204

Hope this helps!

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Mid-West Publishing Company publishes college textbooks. The company operates an 800 telephone number whereby potential adopters
s344n2d4d5 [400]

The various answers to the question are:

  • To answer 90% of calls instantly, the organization needs four extension lines.
  • The average number of extension lines that will be busy is Four
  • For the existing phone system with two extension lines, 34.25 % of calls get a busy signal.

<h3>How many extension lines should be used if the company wants to handle 90% of the calls immediately?</h3>

a)

A number of extension lines needed to accommodate $90 in calls immediately:

Use the calculation for busy k servers.

$$P_{j}=\frac{\frac{\left(\frac{\lambda}{\mu}\right)^{j}}{j !}}{\sum_{i=0}^{k} \frac{\left(\frac{\lambda}{\mu}\right)^{t}}{i !}}$$

The probability that 2 servers are busy:

The likelihood that 2 servers will be busy may be calculated using the formula below.

P_{2}=\frac{\frac{\left(\frac{20}{12}\right)^{2}}{2 !}}{\sum_{i=0}^{2} \frac{\left(\frac{20}{12}\right)^{t}}{i !}}$$\approx 0.3425$

Hence, two lines are insufficient.

The probability that 3 servers are busy:

Assuming 3 lines, the likelihood that 3 servers are busy may be calculated using the formula below.

P_{j}=\frac{\frac{\left(\frac{\lambda}{\mu}\right)^{j}}{j !}}{\sum_{i=0}^{2} \frac{\left(\frac{\lambda}{\mu}\right)^{i}}{i !}}$ \\\\$P_{3}=\frac{\frac{\left(\frac{20}{12}\right)^{3}}{3 !}}{\sum_{i=0}^{3} \frac{\left(\frac{20}{12}\right)^{1}}{i !}}$$\approx 0.1598$

Thus, three lines are insufficient.

The probability that 4 servers are busy:

Assuming 4 lines, the likelihood that 4 of 4 servers are busy may be calculated using the formula below.

P_{j}=\frac{\frac{\left(\frac{\lambda}{\mu}\right)^{j}}{j !}}{\sum_{i=0}^{k} \frac{\left(\frac{\lambda}{\mu}\right)^{t}}{i !}}$ \\\\$P_{4}=\frac{\frac{\left(\frac{20}{12}\right)^{4}}{4 !}}{\sum_{i=0}^{4} \frac{\left(\frac{20}{12}\right)^{7}}{i !}}$

Generally, the equation for is  mathematically given as

To answer 90% of calls instantly, the organization needs four extension lines.

b)

The probability that a call will receive a busy signal if four extensions lines are used is,

P_{4}=\frac{\left(\frac{20}{12}\right)^{4}}{\sum_{i=0}^{4} \frac{\left(\frac{20}{12}\right)^{1}}{i !}} $\approx 0.0624$

Therefore, the average number of extension lines that will be busy is Four

c)

In conclusion, the Percentage of busy calls for a phone system with two extensions:

The likelihood that 2 servers will be busy may be calculated using the formula below.

P_{j}=\frac{\left(\frac{\lambda}{\mu}\right)^{j}}{j !}$$\\\\$P_{2}=\frac{\left(\frac{20}{12}\right)^{2}}{\sum_{i=0}^{2 !} \frac{\left(\frac{20}{12}\right)^{t}}{i !}}$$\approx 0.3425$

For the existing phone system with two extension lines, 34.25 % of calls get a busy signal.

Read more about signal

brainly.com/question/14699772

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3 0
1 year ago
What is the value of 1/4 to the power of 3
LenaWriter [7]

Answer:

1/64

Step-by-step explanation:

hope that helps

7 0
2 years ago
30000mm how much did it grow in a meter
Serggg [28]
30000mm÷10=3000cm
3000cm÷100=30m
Answer: 30m
7 0
2 years ago
Which number line represents the solutions to 1-2x1 = 4?
kaheart [24]

Answer:

Third option: x = -2 and x = 2

Step-by-step explanation:

Given:

|-2x|=4

For a modulus function, if |f(x)|=a, then,

f(x)=\pm a

Here, f(x)=-2x, a=4

∴ -2x=\pm 4\\ -2x=-4\textrm{ or } -2x=4\\ x=\frac{-4}{-2}\textrm{ or }x=\frac{4}{-2}\\ x= 2\textrm{ or }x=-2

Therefore, the third option is the correct answer as the graph has x values as -2 and 2

8 0
3 years ago
Describe the sampling distribution of p(hat). Assume the size of the population is 30,000.
Naya [18.7K]

Answer:

a) \mathbf{\mu_ \hat p = 0.6}

b) \mathbf{\sigma_p =0.01732}

Step-by-step explanation:

Given that:

population mean \mu = 30,000

sample size n = 800

population proportion p = 0.6

a)

The mean of the the sampling distribution is equal to the population proportion.

\mu_ \hat p =  p

\mathbf{\mu_ \hat p = 0.6}

b)

The standard deviation of the sampling distribution can be estimated by using the formula:

\sigma_p = \sqrt{\dfrac{p(1-p)}{n}}

\sigma_p = \sqrt{\dfrac{0.6(1-0.6)}{800}}

\sigma_p = \sqrt{\dfrac{0.6(0.4)}{800}}

\sigma_p = \sqrt{\dfrac{0.24}{800}}

\sigma_p = \sqrt{3 \times 10^{-4}}

\mathbf{\sigma_p =0.01732}

7 0
2 years ago
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