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Soloha48 [4]
3 years ago
14

What is the approximate area of the shaded region in the given square containing 2 semicircles? (Use * 3.14.) 10 cm 0 21.5 squar

e centimeters O 50 square centimeters O 78.5 square centimeters O 100 square centimeters

Mathematics
2 answers:
Crazy boy [7]3 years ago
8 0

Answer:

Subtract the circle from the square

Step-by-step explanation:

(10× 10) - 25pi

lakkis [162]3 years ago
4 0

Answer:

yes

Step-by-step explanation:

bcuz

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While conducting a test of modems being manufactured, it is found that 10 modems were faulty out of a random sample of 367 modem
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Answer:

We conclude that this is an unusually high number of faulty modems.

Step-by-step explanation:

We are given that while conducting a test of modems being manufactured, it is found that 10 modems were faulty out of a random sample of 367 modems.

The probability of obtaining this many bad modems (or more), under the assumptions of typical manufacturing flaws would be 0.013.

Let p = <em><u>population proportion</u></em>.

So, Null Hypothesis, H_0 : p = 0.013      {means that this is an unusually 0.013 proportion of faulty modems}

Alternate Hypothesis, H_A : p > 0.013      {means that this is an unusually high number of faulty modems}

The test statistics that would be used here <u>One-sample z-test</u> for proportions;

                             T.S. =  \frac{\hat p-p}{\sqrt{\frac{p(1-p)}{n} } }  ~  N(0,1)

where, \hat p = sample proportion faulty modems= \frac{10}{367} = 0.027

           n = sample of modems = 367

So, <u><em>the test statistics</em></u>  =  \frac{0.027-0.013}{\sqrt{\frac{0.013(1-0.013)}{367} } }

                                     =  2.367

The value of z-test statistics is 2.367.

Since, we are not given with the level of significance so we assume it to be 5%. <u>Now at 5% level of significance, the z table gives a critical value of 1.645 for the right-tailed test.</u>

Since our test statistics is more than the critical value of z as 2.367 > 1.645, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which <u><em>we reject our null hypothesis</em></u>.

Therefore, we conclude that this is an unusually high number of faulty modems.

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Step-by-step explanation:

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