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MArishka [77]
2 years ago
5

What is the probability that the manufacturing unit has carbon emission beyond the permissible emission level and the test predi

cts this?
Mathematics
1 answer:
lyudmila [28]2 years ago
5 0

The probability that the manufacturing unit has carbon emissions beyond the permissible emission level is 0.2975

Given that the probability that carbon emissions from the company’s factory exceed the permissible level is 35% and the accuracy of the test is 85%.

The possibility of an event or outcome happening contingent on the occurrence of a prior event or outcome is known as conditional probability. The probability of the prior event is multiplied by the current likelihood of the subsequent, or conditional, occurrence to determine the conditional probability.

Event A: The given Carbon emission beyond to the given permissible emission level.

Event B: Test predicts this.

To get the probability of this problem, first we need to divide by 100 the given values.

A=35/100

A=0.35

The probability of event A is P(A)=0.35

And the probability is P(B|A)=85/100=0.85

Now, we will use the conditional probability formula, we get

P(B|A)=P(A∩B)/P(A)

0.85=P(A∩B)/0.35

P(A∩B)=0.85×0.35

P(A∩B)=0.2975

Hence, the probability that the manufacturing unit has carbon emissions beyond the permissible emission level and the test predicts is0.2975.

Learn more about conditional probability from here brainly.com/question/12985746

#SPJ4

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Answer:

There are 6 coins in nickels and 9 coins in quarters.

Step-by-step explanation:

Now, to find the solution.

According to question:

The number of nickels = x.

The number of quarters = y.

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x+y=15.

He had 3 more quarters than nickels.

Thus,

y=x+3 .....(1)

Now, to get the solution:

x+y=15

Substituting the equation (1):

x+(x+3)=15

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2x+3=15

<em>Subtracting both sides by 3 we get:</em>

<em />2x=12<em />

<em>Dividing both sides by 2 we get:</em>

x=6.

<em>The number of nickels = 6.</em>

Now, substituting the value of x in equation (1):

y=x+3\\\\y=6+3\\\\y=9.

<em>The number of quarters = 9.</em>

Thus, there are 6 coins in nickels and 9 coins in quarters.

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Hope this helps !

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Suppose a production line operates with a mean filling weight of 16 ounces per container. Since over- or under-filling can be da
miss Akunina [59]

Answer:

From the question we are told that

   The  population mean is  \mu  =  16

    The sample size is  n  =  30  

     The  sample mean is  \= x =  16.32

     The  population standard deviation is  \sigma  =  0.8

      The  level of significance is  \alpha  = 0.10

Step 1: State hypotheses:

The  null hypothesis is  H_o :  \mu = 16

The alternative hypothesis is  H_a :  \mu \ne  16

Step 2: State the test statistic. Since we know the population standard deviation and the sample is large our test statistics is

          t = \frac{ \= x  -\mu }{ \frac{\sigma}{ \sqrt{n} } }

=>       t = \frac{ 16.32  -16  }{ \frac{0.8 }{ \sqrt{30} } }

=>       t =2.191

Generally the degree of freedom is mathematically represented as

          df  =  n - 1

=>      df  =  30  - 1

=>      df  =29

Step 3: State the critical region(s):

From the student t-distribution table the critical value corresponding to  \alpha  = 0.10  is

         t = 1.311

Generally the critical regions is mathematically represented as  

         - 1.311 < T <  1.311

Step 4: Conduct the experiment/study:

Generally the from the value obtained we see that the t value is outside the critical region so  the decision is [Reject the null hypothesis ]  

Step 5: Reach conclusions and state in English:

  There is  sufficient evidence to show that the filling weight has to be adjusted

Step 6: Calculate the p-value associated with this test. How does this the p-value support your conclusions in Step 5?

From the student t-distribution table the probability value to the right corresponding to t =2.191 at  a degree of freedom of  df  =29  is

        P( t > 2.191) =  0.0183

Generally the p-value is mathematically represented as

       p-value  = 2 * P( t >  2.191 )

=>    p-value  = 2 * 0.0183

=>    p-value  =  0.0366

Generally  looking at the value obtained we see that p- value <  \alpha hence

The decision rule is

Reject the null hypothesis

Step-by-step explanation:

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