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dusya [7]
3 years ago
12

Solve for x.(x-1)(5x-4)=0

Mathematics
2 answers:
Monica [59]3 years ago
7 0
Since the equation is already factored set each factor equal to zero and solve.
x - 1 = 0
Add 1 to both sides
x = 1

5x - 4 = 0
Add 4 to both sides
5x = 4
Divide both sides by 5
x = 4/5
Gre4nikov [31]3 years ago
5 0
(x - 1) (5x - 4) = 0

x - 1 = 0
  + 1 + 1
-----------
     x = 1

5x - 4 = 0
    + 4 + 4
-------------
5x(/5) = 4(/5)

x = 4/5

So: x = 4/5 or 1. There are two possible answers to this equation.

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(-3x +11x-1)+(7x2 - 4x+4)
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Step-by-step explanation:

-3x + 11x - 1 + 7x2 - 4x + 4

Solving like terms

7x2 + 4x + 3

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3x - y = 7 6x - y = 10 When solving this system of equations by elimination, which could be the resulting equation when a variab
max2010maxim [7]
It depends on which variable is eliminated.

If you multiply the second equation by -1 and eliminate the y:
3x - y = 7
-6x + y = -10
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6 0
3 years ago
Solve <br> 2x-10=2 6 for x
strojnjashka [21]

Answer:

x=18

Step-by-step explanation:

isolate x to one side of the equation:

2x=26+10

2x = 36

divide by 2 for both sides

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8 0
2 years ago
An automobile manufacturer finds that 1 in every 2500 automobiles produced has a particular manufacturing defect. ​(a) Use a bin
Advocard [28]

Answer:

a) 0.1558 = 15.58% probability of finding 4 cars with the defect in a random sample of 7000 cars.

b) 0.1557 = 15.57% probability of finding 4 cars with the defect in a random sample of 7000 cars. These probabilities are very close, which means that the approximation works.

Step-by-step explanation:

Binomial distribution:

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

Poisson distribution:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

In which

x is the number of sucesses

e = 2.71828 is the Euler number

\mu is the mean in the given interval.

To use the Poisson approximation for the binomial, we have that:

\mu = np

1 in every 2500 automobiles produced has a particular manufacturing defect.

This means that p = \frac{1}{2500} = 0.0004

a) Use a binomial distribution to find the probability of finding 4 cars with the defect in a random sample of 7000 cars.

This is P(X = 4) when n = 7000. So

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 4) = C_{7000,4}.(0.0004)^{4}.(0.9996)^{6996} = 0.1558

0.1558 = 15.58% probability of finding 4 cars with the defect in a random sample of 7000 cars.

(b) The Poisson distribution can be used to approximate the binomial distribution for large values of n and small values of p.

Using the approximation:

\mu = np = 7000*0.0004 = 2.8. So

P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}

P(X = 4) = \frac{e^{-2.8}*(2.8)^{4}}{(4)!} = 0.1557

0.1557 = 15.57% probability of finding 4 cars with the defect in a random sample of 7000 cars. These probabilities are very close, which means that the approximation works.

6 0
3 years ago
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