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jasenka [17]
3 years ago
5

7/8 + 9/16 Show your work

Mathematics
2 answers:
Harman [31]3 years ago
8 0
7/8 = 14/16
14/16 + 9/16 = 23/16
ololo11 [35]3 years ago
5 0
First, we have to make them like terms. so just multiply the first equation by 2/2, which is really just 1.

Making it 14/16 + 9/16.

then, simply add,

23/16

in mixed number, it is 1 7/16
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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
If the probability of a student spending time reading is 0.10, the probability of spending time watching TV is 0.90 and the prob
joja [24]

Answer:

The probability is 0.97

Step-by-step explanation:

In this question, we are concerned with calculating the probability of a student spending time reading or watching TV.

To calculate this, we simply use a direct mathematical formula.

P( of spending time reading or watching tv) = P(of spending time reading) + P(spending time watching Tv) - P( of spending time watching Tv and reading)

From the question, we identify the probabilities as follows;

P(spending time reading) = 0.1

P(of spending time watching Tv) = 0.9

P(of spending time watching Tv and reading) = 0.03

Now, plugging these values, we have

P( of spending time reading or watching Tv) = 0.9 + 0.1 -0.03

= 1-0.03 = 0.97

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3 years ago
∠A and \angle B∠B are complementary angles. If m\angle A=(2x+30)^{\circ}∠A=(2x+30)
egoroff_w [7]

Answer:

x =21

Step-by-step explanation:

So we know that:

And that the two angles are vertical angles.

Since they are vertical angles, their measurements are equivalent. Thus, to find x, set the equations equal to each other:

Now, solve for x. Add 30 to both sides. The left side cancels:

Now, subtract 2x from both sides. The right cancels:

Thus, the value of x is 21.

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3 years ago
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dem82 [27]

Answer:

71

Step-by-step explanation:

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71

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Answer:

13.5

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