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alexgriva [62]
4 years ago
15

Enter the value of n so that the expression (-y + 5) + (7y - 9) is equivalent to (ny - 4)

Mathematics
1 answer:
kvasek [131]4 years ago
6 0
The answer is :
n = 6
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3 years ago
Suppose the probability of being infected with a certain virus is 0.001. A test used to detect the virus is positive 99% of the
charle [14.2K]

Answer:

P (A ║ B)  = 1.98 %

Step-by-step explanation:

Bayes´ Theorem  express

P (A ║ B)  =  P(A) * P( B ║ A) / P(B)

Now we identify

Event A  person infected with a virus. Probability of being infected by a virus is  P/A)  0.001

Event B  the test was positive. Probability of test positive  P(B)  = 0,05

Probability of  P ( B║ A)  is the porbability of test positive given that is infected   = 0.99

Then by subtitution in a general equation of the theorem we have

P (A ║ B)  =  0.001*0.99/ 0.05

P (A ║ B)  =  0.0198          P (A ║ B)  = 1.98 %

5 0
4 years ago
Read 2 more answers
Susan is taking Western Civilization this semester on a pass/fail basis. The department teaching the course has a history of pas
Volgvan

Answer:

a. P(n) = 0.85 * (0.15)^(n-1)

b. P(n=1) = 0.85

c. P(n= 2) = 0.1275

d. P(n≥3) = 0.0225

e. Expected number of attempts is 1.176

Step-by-step explanation:

a.

Given

p = success = 85% = 0.85

q = failure = 1 - q = 1 - 0.85 = 0.15

The results of passing/failing takes a Bernoulli distribution

Since, there are independent trials

The number of trials until the first successful event occurs is given by

P(n = k) = p . (1 - p)^(k-1)

P(n = k) = p.q^(k-1)

This is so because it is a Bernoulli distribution and it is modeled by a geometric distribution.

Substitute 0.85 for p

P(n) = 0.85 * (0.15)^(n-1)

b.

Given

n = 1

Using P(n=1) = 0.85 * (0.15)^(n-1)

P(1) = 0.85 * 0.15^(1-1)

P(1) = 0.85 * 0.15°

P(1) = 0.85 * 1

P(1) = 0.85

Therefore, the probability that Susan passes on the first try is 0.85.

c.

n = 2

Using P(n=2) = 0.85 * (0.15)^(2-1)

P(2) = 0.85 * 0.15^(2-1)

P(2) = 0.85 * 0.15¹

P(2) = 0.85 * 0.15

P(2) = 0.1275

Therefore, the probability that Susan passes on the first try is 0.1275

d.

We'll make use of the probability of Susan passing the course after an infinite number of trials is 1.

i.e.

P(n=1) + P(n=2) + P(n=3) + P(n=4) + ......... = 1 --- This is then simplified to

P(n=1) + P(n=2) + P(n≥3) = 1

P(n≥3) = 1 - P(n=1) - P(n=2)

P(n≥3) = 1 - 0.85 - 0.1275

P(n≥3) = 0.0225

Therefore, the probability that Susan needs at least 3 attempts to pass is 0.0225

e.

In (a) above, we explained that the distribution is modeled by an exponential distribution.

The Expected Value for this is inverse of p, where p = 0.85

So, E(n) = 1/p

E(n) = 1/0.85

E(n) = 1.176470588235294

E(n) = 1.176 --- Approximated

Hence the Expected number of attempts is 1.176

7 0
4 years ago
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