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Bingel [31]
3 years ago
13

16. Jerome is a co-owner of a small company and received 1/3 of the company’s profits this year. What were the company’s overall

profits if Jerome made $150,000? Write an equation and solve
Mathematics
1 answer:
AlekseyPX3 years ago
6 0
Remark
The trick to this question is realizing what you took 1/3 of. Did you take it of the 150000 or is it 1/3 of some total you have to find. I don't think you could come up with a third choice. 

It turns out that the answer is 1/3 of a number you don't know.

Equation
(1/3) x = 150000 Multiply both sides by 3
3*(1/3) x = 150000 * 3
x = 150000 * 3
x = 450000

Conclusion
The amount the company makes is 450000 dollars / year.
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What is the equation for this
Lelechka [254]
164÷2=82
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so therefore Edwin drove 164-117=47
4 0
3 years ago
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The U.S. Bureau of Labor Statistics released hourly wage figures for various countries for workers in the manufacturing sector.
elena-14-01-66 [18.8K]

Answer:

(a) The probability that the sample average will be between $30.00 and $31.00 is 0.5539.

(b) The probability that the sample average will exceed $21.00 is 0.12924.

(c) The probability that the sample average will be less than $22.80 is 0.04006.

Step-by-step explanation:

We are given that the hourly wage was $30.67 for Switzerland, $20.20 for Japan, and $23.82 for the U.S.

Assume that in all three countries, the standard deviation of hourly labor rates is $4.00.

(a) Suppose 40 manufacturing workers are selected randomly from across Switzerland.

Let \bar X = <u>sample average wage</u>

The z score probability distribution for sample mean is given by;

                                Z  =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } ~ N(0,1)

where, \mu = population mean wage for Switzerland = $30.67

            \sigma = standard deviation = $4.00

            n = sample of workers selected from across Switzerland = 40

Now, the probability that the sample average will be between $30.00 and $31.00 is given by = P($30.00 < \bar X < $31.00)

        P($30.00 < \bar X < $31.00) = P(\bar X < $31.00) - P(\bar X \leq $30.00)

        P(\bar X < $31) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } < \frac{31-30.67}{\frac{4}{\sqrt{40} } } ) = P(Z < 0.52) = 0.69847

        P(\bar X \leq $30) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } \leq \frac{30-30.67}{\frac{4}{\sqrt{40} } } ) = P(Z \leq -1.06) = 1 - P(Z < 1.06)

                                                             = 1 - 0.85543 = 0.14457

<em>The above probability is calculated by looking at the value of x = 0.52 and x = 1.06 in the z table which has an area of 0.69847 and 0.85543 respectively.</em>

Therefore, P($30.00 < \bar X < $31.00) = 0.69847 - 0.14457 = <u>0.5539</u>

<u></u>

(b) Suppose 32 manufacturing workers are selected randomly from across Japan.

Let \bar X = <u>sample average wage</u>

The z score probability distribution for sample mean is given by;

                                Z  =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } ~ N(0,1)

where, \mu = population mean wage for Japan = $20.20

            \sigma = standard deviation = $4.00

            n = sample of workers selected from across Japan = 32

Now, the probability that the sample average will exceed $21.00 is given by = P(\bar X > $21.00)

        P(\bar X > $21) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } > \frac{21-20.20}{\frac{4}{\sqrt{32} } } ) = P(Z > 1.13) = 1 - P(Z < 1.13)

                                                          = 1 - 0.87076 = <u>0.12924</u>

<em />

<em>The above probability is calculated by looking at the value of x = 1.13 in the z table which has an area of 0.87076.</em>

<em />

(c) Suppose 47 manufacturing workers are selected randomly from across United States.

Let \bar X = <u>sample average wage</u>

The z score probability distribution for sample mean is given by;

                                Z  =  \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } ~ N(0,1)

where, \mu = population mean wage for United States = $23.82

            \sigma = standard deviation = $4.00

            n = sample of workers selected from across United States = 47

Now, the probability that the sample average will be less than $22.80 is given by = P(\bar X < $22.80)

  P(\bar X < $22.80) = P( \frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } } < \frac{22.80-23.82}{\frac{4}{\sqrt{47} } } ) = P(Z < -1.75) = 1 - P(Z \leq 1.75)

                                                               = 1 - 0.95994 = <u>0.04006</u>

<em />

<em>The above probability is calculated by looking at the value of x = 1.75 in the z table which has an area of 0.95994.</em>

3 0
3 years ago
A sampling frame a. is a list of population elements from which the sample will be drawn. b. is the list of population elements
olga2289 [7]

Answer:

<h2> A. is a list of population elements from which the sample will be drawn</h2>

Step-by-step explanation:

Sampling frame is the list of people or items from which a sample is taken.  

Sampling is used because it is almost impossible to study entire population. Sampling allows us to find information about a population on the basis of results from a subset of the population, without studying every individual. It is easier and cost effective process.

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What number is 38% of 60
atroni [7]

Answer:

63.333333333333 you could put 63.3

Step-by-step explanation:

How much is 38 out of 60 written as a percent value? Convert fraction (ratio) 38 / 60 Answer: 63.333333333333%

3 0
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William sunk 25% of the shots he made on the basket. If he threw 80 shots, how many did he miss?
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Answer:

Step-by-step explanation:

He missed 20 shots

Write 25% as 25100.

25100 of 80 = 25100 × 80.

Therefore, the answer is 20.

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2 years ago
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