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astraxan [27]
3 years ago
15

My tens digit is less than 7. I am one away from being a multiple of 5. If you half me you will not get a whole number. Who am I

? A.883B.429C.133D.524E.635F.236G.712H.671

Mathematics
2 answers:
Hitman42 [59]3 years ago
8 0
Hope this helps, can i get brainliest please

Len [333]3 years ago
6 0

Answer:

its B.429

Step-by-step explanation:

20<70

429+1=multiple of 5

429÷2=214.5

so the answer is 429

 

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2.5% of a population are infected with a certain disease. There is a test for the disease, however the test is not completely ac
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Answer:

P(disease/positivetest) = 0.36116

Step-by-step explanation:

This is a conditional probability exercise.

Let's name the events :

I : ''A person is infected''

NI : ''A person is not infected''

PT : ''The test is positive''

NT : ''The test is negative''

The conditional probability equation is :

Given two events A and B :

P(A/B) = P(A ∩ B) / P(B)

P(B) >0

P(A/B) is the probability of the event A given that the event B happened

P(A ∩ B) is the probability of the event (A ∩ B)

(A ∩ B) is the event where A and B happened at the same time

In the exercise :

P(I)=0.025

P(NI)= 1-P(I)=1-0.025=0.975\\P(NI)=0.975

P(PT/I)=0.904\\P(PT/NI)=0.041

We are looking for P(I/PT) :

P(I/PT)=P(I∩ PT)/ P(PT)

P(PT/I)=0.904

P(PT/I)=P(PT∩ I)/P(I)

0.904=P(PT∩ I)/0.025

P(PT∩ I)=0.904 x 0.025

P(PT∩ I) = 0.0226

P(PT/NI)=0.041

P(PT/NI)=P(PT∩ NI)/P(NI)

0.041=P(PT∩ NI)/0.975

P(PT∩ NI) = 0.041 x 0.975

P(PT∩ NI) = 0.039975

P(PT) = P(PT∩ I)+P(PT∩ NI)

P(PT)= 0.0226 + 0.039975

P(PT) = 0.062575

P(I/PT) = P(PT∩I)/P(PT)

P(I/PT)=\frac{0.0226}{0.062575} \\P(I/PT)=0.36116

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Answer:

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And the probability of loss with the first wersion is 0.729

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And the probability of loss with the first wersion is 0.774

As we can see the best alternative is the first version since the probability of loss is lower than the probability of loss on version 2.

Step-by-step explanation:

Previous concepts

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

Solution to the problem

Alternative 1

Let X the random variable of interest, on this case we now that:

X \sim Binom(n=3, p=0.1)

The probability mass function for the Binomial distribution is given as:

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Where (nCx) means combinatory and it's given by this formula:

nCx=\frac{n!}{(n-x)! x!}

We can find the probability of loss like this P(X=0) and if we find this probability we got this:

P(X=0)=(3C0)(0.1)^0 (1-0.1)^{3-0}=0.729

And the probability of loss with the first wersion is 0.729

Alternative 2

Let Y the random variable of interest, on this case we now that:

Y \sim Binom(n=5, p=0.05)

The probability mass function for the Binomial distribution is given as:

P(Y)=(nCy)(p)^y (1-p)^{n-y}

Where (nCx) means combinatory and it's given by this formula:

nCy=\frac{n!}{(n-y)! y!}

We can find the probability of loss like this P(Y=0) and if we find this probability we got this:

P(Y=0)=(5C0)(0.05)^0 (1-0.05)^{5-0}=0.774

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As we can see the best alternative is the first version since the probability of loss is lower than the probability of loss on version 2.

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