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Lisa [10]
3 years ago
12

The volume V of a cylinder is computed using the values 8.8m for the diameter and 5.8m for the height. Use the linear approximat

ion to estimate the maximum error in V if each of these values has a possible error of at most 8%.
Mathematics
1 answer:
Delvig [45]3 years ago
5 0

Answer:

The maximum error is approximately Ev=24%

Step-by-step explanation:

the volume of the cylinder V is

V= π/4*H*D²

where H= height and D= diameter

the variation of V will be

dV = (∂V/∂H)*dH + (∂V/∂D)*dD

dV = π/4*D²*dH  +π/2*H*D*dD

if we divide by the volume V

dV /V  = (π/4*D²*dH  +π/2*H*D*dD )/( π/4*H*D²) = dH/H + 2*dD/D

dV /V =  dH/H + 2*dD/D

then we can approximate

error in V= Ev= ΔV/V ≈ dV/V

error in H= Eh=ΔH/H ≈ dH/H

error in D= Ed=ΔD/D ≈ dD/D

thus

Ev= Eh + 2*Ed

since Ed=Eh=E=8%

Ev=  Eh + 2*Ed =3*E=3*8%=24%

Ev= 24%

therefore the maximum error is approximately Ev=24%

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Find the value of x so that L is parallel to M. State the converse used!
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<h3>6 degrees</h3>

Step-by-step explanation

Find the diagram attached. In Line geometry, there is a theorem that states that the sum of the adjacent interior angles is 180 degrees. According to the diagram, the adjacent interior angles are 7x- 15 and 24x + 9.

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5 0
4 years ago
What is the probability that a random person who tests positive for a certain blood disease actually has the disease, if we know
xeze [42]

Answer:

Step-by-step explanation:

Hello!

Any medical test used to detect certain sicknesses have several probabilities associated with their results.

Positive (test is +) ⇒ P(+)

True positive (test is + and the patient is sick) ⇒ P(+ ∩ S)

False-positive (test is + but the patient is healthy) ⇒P(+ ∩ H)

Negative (test is -) ⇒ P(-)

True negative (test is - and the patient is healthy) ⇒ P(- ∩ H)

False-negative (test is - but the patient is sick) ⇒ P(- ∩ S)

The sensibility of the test is defined as the capacity of the test to detect the sickness in sick patients (true  positive rate).

⇒ P(+/S) =<u> P(+ ∩ S)  </u>

                    P(S)

The specificity of the test is the capacity of the test to have a negative result when the patients are truly  healthy (true negative rate)

⇒ P(-/H) =<u> P(- ∩ H)  </u>

                   P(H)

For this particular blood disease the following probabilities are known:

1% of the population has the disease: P(S)= 0.01

95% of those who are sick, test positive for it: P(+/S)= 0.95 (sensibility of the test)

2% of those who don't have the disease, test positive for it: P(+/H)= 0.02

The probability of a person having the blood sickness given that the test was positive is:

P(S/+)= <u> P(+ ∩ S)  </u>

                P(+)

The first step you need to calculate the intersection between both events + and S, for that you will use the information about the sickness prevalence in the population and the sensibility of the test:

P(+/S) =<u> P(+ ∩ S) </u>

                 P(S)

P(+/S)* P(S)  = P(+ ∩ S)  

P(+ ∩ S) = 0.95*0.01= 0.0095

The second step is to calculate the probability of the test being positive:

P(+)=  P(+ ∩ S) +  P(+ ∩ H)

Now we know that 1% of the population has the blood sickness, wich means that 99% of the population doesn't have it, symbolically: P(H)= 0.99

Then you can clear the value of P(+ ∩ H):

P(+/H) =<u> P(+ ∩ H) </u>

                 P(H)

P(+/H)*P(H)  = P(+ ∩ H)

P(+ ∩ H) = 0.02*0.99= 0.0198

Next you can calculate P(+):

P(+)=  P(+ ∩ S) +  P(+ ∩ H)= 0.0095 + 0.0198= 0.0293

Now you can calculate the asked probability:

P(S/+)= <u> P(+ ∩ S)  </u> =<u> 0.0095 </u>= 0.32

                P(+)        0.0293

I hope it helps!

                 

                 

6 0
3 years ago
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