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svetlana [45]
4 years ago
13

An automobile manufacturer obtains the microprocessors used to regulate fuel consumption in its automobiles from three microelec

tronic firms: A, B, and C. The quality-control department of the company has determined that 6% of the microprocessors produced by firm A are defective, 7% of those produced by firm B are defective, and 5.5% of those produced by firm C are defective. Firms A, B, and C supply 45%, 30%, and 25%, respectively, of the microprocessors used by the company. What is the probability that a randomly selected automobile manufactured by the company will have a defective microprocessor?
Mathematics
1 answer:
Anastaziya [24]4 years ago
5 0

Answer:

The probability that a randomly selected automobile manufactured by the company will have a defective microprocessor is 6.2 %.

Step-by-step explanation:

Given:

The probability of getting a microprocessor from firm A is, P(A)=45\%=0.45

The probability of getting a microprocessor from firm B is, P(B)=30\%=0.30

The probability of getting a microprocessor from firm C is, P(C)=25\%=0.25

Now, let event D be having a defective microprocessor at random.

So, as per the question,

Probability of producing a defective microprocessor from firm A is, P(D/A)=6\%=0.06

Probability of producing a defective microprocessor from firm B is, P(D/B)=7\%=0.07

Probability of producing a defective microprocessor from firm C is, P(D/C)=5.5\%=0.055

Now, probability of having a defective microprocessor when selected at random is given as:

P(D)=P(A)\cdot P(D/A)+P(B)\cdot P(D/B)+P(C)\cdot P(D/C)\\P(D)=(0.45\times 0.06)+(0.30\times 0.07)+(0.25\times 0.055)\\P(D)=0.027+0.021+0.01375\\P(D)=0.06175\ or\ P(D)=0.06175\times 100\approx 6.2\%

Therefore, the probability that a randomly selected automobile manufactured by the company will have a defective microprocessor is 6.2 %.

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$1440

Step-by-step explanation:

First, find the unit rate by dividing 300 by 5, which equals 60. So, Kendra earns $60 in one day. Then, multiply 60 by 24, which equals 1440. So, Kendra makes $1440 in 24 days. Hope this helped!

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<h2>60 cm^2</h2>

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Let ,

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Hope this helps ....

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Cable Strength: A group of engineers developed a new design for a steel cable. They need to estimate the amount of weight the ca
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Answer:

95% confidence interval for the mean breaking strength of the new steel cable is [763.65 lb , 772.75 lb].

Step-by-step explanation:

We are given that the engineers take a random sample of 45 cables and apply weights to each of them until they break. The mean breaking weight for the 45 cables is 768.2 lb. The standard deviation of the breaking weight for the sample is 15.1 lb.

Since, in the question it is not specified that how much confidence interval has be constructed; so we assume to be constructing of 95% confidence interval.

Firstly, the Pivotal quantity for 95% confidence interval for the population mean is given by;

                            P.Q. =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample mean breaking weight = 768.2 lb

            s = sample standard deviation = 15.1 lb

            n = sample of cables = 45

            \mu = population mean breaking strength

Here for constructing 95% confidence interval we have used One-sample t test statistics as we don't know about population standard deviation.

<u>So, 95% confidence interval for the population mean, </u>\mu<u> is ;</u>

P(-2.02 < t_4_4 < 2.02) = 0.95  {As the critical value of t at 44 degree

                                           of freedom are -2.02 & 2.02 with P = 2.5%}  

P(-2.02 < \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } } < 2.02) = 0.95

P( -2.02 \times {\frac{s}{\sqrt{n} } } < {\bar X-\mu} < 2.02 \times {\frac{s}{\sqrt{n} } } ) = 0.95

P( \bar X-2.02 \times {\frac{s}{\sqrt{n} } } < \mu < \bar X+2.02 \times {\frac{s}{\sqrt{n} } } ) = 0.95

<u>95% confidence interval for</u> \mu = [ \bar X-2.02 \times {\frac{s}{\sqrt{n} } } , \bar X+2.02 \times {\frac{s}{\sqrt{n} } } ]

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Therefore, 95% confidence interval for the mean breaking strength of the new steel cable is [763.65 lb , 772.75 lb].

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