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uranmaximum [27]
3 years ago
14

A man walks for x hours at a speed of

Mathematics
1 answer:
alexandr1967 [171]3 years ago
3 0

Given:

A man walks for x hours at a speed of  (x + 1) km/h and cycles for (x - 1) hours at  a speed of (2x + 5) km/h.

Total distance  travelled is 90 km.

To find:

The value of x.

Solution:

We know that,

Speed=\dfrac{Distance}{Time}

Speed\times Time=Distance

A man walks for x hours at a speed of  (x + 1) km/h, so walking distance is

D_1=(x+1)(x) km

The man cycles for (x - 1) hours at  a speed of (2x + 5) km/h, so the cycling distance is

D_2=(2x+5)(x-1) km

Now,

Total distance = 90 km

D_1+D_2=90

(x+1)x+(2x+5)(x-1)=90

x^2+x+2x^2-2x+5x-5-90=0

3x^2+4x-95=0

3x^2+19x-15x-95=0

x(3x+19)-5(3x+19)=0

(3x+19)(x-5)=0

3x+19=0\text{ and }x-5=0

x=\dfrac{-19}{3}\text{ and }x=5

Time cannot be negative. So, the only possible value of x is 5.

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Suppose that bugs are present in 1% of all computer programs. A computer de-bugging program detects an actual bug with probabili
lawyer [7]

Answer:

(i) The probability that there is a bug in the program given that the de-bugging program has detected the bug is 0.3333.

(ii) The probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is 0.1111.

(iii) The probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is 0.037.

Step-by-step explanation:

Denote the events as follows:

<em>B</em> = bugs are present in a computer program.

<em>D</em> = a de-bugging program detects the bug.

The information provided is:

P(B) =0.01\\P(D|B)=0.99\\P(D|B^{c})=0.02

(i)

The probability that there is a bug in the program given that the de-bugging program has detected the bug is, P (B | D).

The Bayes' theorem states that the conditional probability of an event <em>E </em>given that another event <em>X</em> has already occurred is:

P(E|X)=\frac{P(X|E)P(E)}{P(X|E)P(E)+P(X|E^{c})P(E^{c})}

Use the Bayes' theorem to compute the value of P (B | D) as follows:

P(B|D)=\frac{P(D|B)P(B)}{P(D|B)P(B)+P(D|B^{c})P(B^{c})}=\frac{(0.99\times 0.01)}{(0.99\times 0.01)+(0.02\times (1-0.01))}=0.3333

Thus, the probability that there is a bug in the program given that the de-bugging program has detected the bug is 0.3333.

(ii)

The probability that a bug is actually present given that the de-bugging program claims that bug is present is:

P (B|D) = 0.3333

Now it is provided that two tests are performed on the program A.

Both the test are independent of each other.

The probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is:

P (Bugs are actually present | Detects on both test) = P (B|D) × P (B|D)

                                                                                     =0.3333\times 0.3333\\=0.11108889\\\approx 0.1111

Thus, the probability that the bug is actually present given that the de-bugging program claims that bugs are present on both the first and second tests is 0.1111.

(iii)

Now it is provided that three tests are performed on the program A.

All the three tests are independent of each other.

The probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is:

P (Bugs are actually present | Detects on all 3 test)

= P (B|D) × P (B|D) × P (B|D)

=0.3333\times 0.3333\times 0.3333\\=0.037025927037\\\approx 0.037

Thus, the probability that the bug is actually present given that the de-bugging program claims that bugs are present on all three tests is 0.037.

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Step-by-step explanation:

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