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Temka [501]
3 years ago
14

John is a pizza delivery driver. He makes $12.25 an hour. John has $100 in his bank account. He wants to purchase a flat screen

TV on sale at Best Buy for $179.99. How many hours will have to work to be able to have enough money in his bank account to purchase the TV.
Mathematics
2 answers:
ipn [44]3 years ago
5 0

Answer: I believe it would be 7 hours.  

Step-by-step explanation: He already had $100 in his bank account so he would only need to work to pay off the remainder of the cost. So, if you do $179.99-$100 you get the remainder which is $79.99. Then you would divide $79.99 by $12.25 (his hourly pay) to find the amount of hours he would have to work. It was about 6.5 hours but you can't work for half an hour, so you would round up to 7 hours total to have enough money to pay for the TV.

I hope this helped!! Good luck :)    

Nataliya [291]3 years ago
4 0

Answer:

7 hours

Step-by-step explanation:

John already has $100 in his account if he works for 7 hours he will make $85.75 which is more than enough and he will have $185.75. If he worked for 6 hours he will make only $73.50. Which then he will have $173.50. So that is why the answer is 7 hours.

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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>

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Answer:

6

Step-by-step explanation:

One fourth is ÷4

24÷4=6

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