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zepelin [54]
3 years ago
5

the partial factorization of 2 x - 3 x - 10 is modeled with algebra tiles which unit tiles are needed to complete the factorizat

ion

Mathematics
1 answer:
nikklg [1K]3 years ago
3 0
The partial factorization of 2 x - 3 x - 10 is modeled with algebra tiles is that you will need 2 x tiles and 4 negative 1 tiles and 3 positive 1 tiles.
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The quotient of 36 and 3 is j
MaRussiya [10]

the answer is 12 because

36÷12=3

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4 years ago
Please help!<br> Which ordered pair is the solution to the system of equations?
torisob [31]
The answer to the question

5 0
3 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
Help ASAP 20 POINTS!!!!!!!<br><br> (6 x 10^-2) divided by (8 x 10^7)
Naddika [18.5K]
6.6
×
10
−
8
3.3
×
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−
4
=
2
×
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Explanation:
6.6
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10
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3.3
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6.6
3.3
×
10
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8
10
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4
=
2
×
10
(
−
8
)
−
(
−
4
)
- as
a
m
a
n
=
a
m
−
n
=
2
×
10
−
8
+
4
=
2
×
10
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4
8 0
2 years ago
Which is the value of 1/4 of 1760??
Serga [27]

Hello,

1 760 * 1 / 4 = 440

Bye ;)

6 0
3 years ago
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