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zimovet [89]
3 years ago
13

Can someone please help me....?

Mathematics
1 answer:
leonid [27]3 years ago
8 0

9514 1404 393

Answer:

  input: 0 or -4

Step-by-step explanation:

<u>Given</u>:

  c(y) = y² +4y

<u>Find</u>:

  y such that c(y) = 0

<u>Solution</u>:

  0 = y² +4y . . . . . desired condition

  0 = y(y +4) . . . . . factor

We have the product of two factors. The "zero product rule" tells us that the product is only zero if one or more of the factors is zero.

  y = 0 . . . . . makes the factor y be zero

  y = -4 . . . . . makes the factor (y+4) be zero

The inputs you're looking for are 0 or -4.

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If 90 percent of automobiles in Orange County have both headlights working, what is the probability that in a sample of eight au
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Answer:

P(X \geq 7) = P(X=7) +P(X=8)

And we can find the individual probabilities using the probability mass function

P(X=7)=(8C7)(0.9)^7 (1-0.9)^{8-7}=0.3826  

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And replacing we got:

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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

Let X the random variable of interest "number of automobiles with both headligths working", on this case we now that:  

X \sim Binom(n=8, p=0.9)  

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

P(X)=(nCx)(p)^x (1-p)^{n-x}  

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

nCx=\frac{n!}{(n-x)! x!}  

And for this case we want to find this probability:

P(X \geq 7) = P(X=7) +P(X=8)

And we can find the individual probabilities using the probability mass function

P(X=7)=(8C7)(0.9)^7 (1-0.9)^{8-7}=0.3826  

P(X=8)=(8C8)(0.9)^8 (1-0.9)^{8-8}=0.4305  

And replacing we got:

P(X \geq 7) = P(X=7) +P(X=8)=0.3826 +0.4305=0.8131

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