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lutik1710 [3]
2 years ago
13

HelpThere is 2A+B and 2A-B can someone help to find A and B.​

Mathematics
1 answer:
skelet666 [1.2K]2 years ago
6 0

Answer:

3789)√××{2664863 %/++631%

5545845433%

8766461%. -/

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Answer:

The Radius is 7.5, the Diameter is 15, as you are just doubling the Radius

Step-by-step explanation:

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What is -4x with an exponent of zero?
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Answer

-4

Step-by-step explanation:

x^0 = 1

so -4x^0

= -4

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Denton owns a bookstore. Today he sold books for $112, $93, $131, $64 and $210. Estimate the total value of the five book sales.
jonny [76]
In the end it should be 610 dollars
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The number of surface flaws in plastic panels used in the interior of automobiles has a Poisson distribution with a mean of 0.08
kvv77 [185]

Answer:

a) 44.93% probability that there are no surface flaws in an auto's interior

b) 0.03% probability that none of the 10 cars has any surface flaws

c) 0.44% probability that at most 1 car has any surface flaws

Step-by-step explanation:

To solve this question, we need to understand the Poisson and the binomial probability distributions.

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.

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 with a mean of 0.08 flaws per square foot of plastic panel. Assume an automobile interior contains 10 square feet of plastic panel.

So \mu = 10*0.08 = 0.8

(a) What is the probability that there are no surface flaws in an auto's interior?

Single car, so Poisson distribution. This is P(X = 0).

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

P(X = 0) = \frac{e^{-0.8}*(0.8)^{0}}{(0)!} = 0.4493

44.93% probability that there are no surface flaws in an auto's interior

(b) If 10 cars are sold to a rental company, what is the probability that none of the 10 cars has any surface flaws?

For each car, there is a p = 0.4493 probability of having no surface flaws. 10 cars, so n = 10. This is P(X = 10), binomial, since there are multiple cars and each of them has the same probability of not having a surface defect.

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

P(X = 10) = C_{10,10}.(0.4493)^{10}.(0.5507)^{0} = 0.0003

0.03% probability that none of the 10 cars has any surface flaws

(c) If 10 cars are sold to a rental company, what is the probability that at most 1 car has any surface flaws?

At least 9 cars without surface flaws. So

P(X \geq 9) = P(X = 9) + P(X = 10)

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

P(X = 9) = C_{10,9}.(0.4493)^{9}.(0.5507)^{1} = 0.0041

P(X = 10) = C_{10,10}.(0.4493)^{10}.(0.5507)^{0} = 0.0003

P(X \geq 9) = P(X = 9) + P(X = 10) = 0.0041 + 0.0003 = 0.0044

0.44% probability that at most 1 car has any surface flaws

5 0
3 years ago
Find the difference. (9/x^2-9x)-(6/x^2-81)
Sunny_sXe [5.5K]

The difference is  $\frac{3 x+81}{x(x-9)(x+9)}$

Explanation:

The expression is $\left(\frac{9}{x^{2}-9 x}\right)-\left(\frac{6}{x^{2}-81}\right)$

Removing the parenthesis, we have,

$\left\frac{9}{x^{2}-9 x}\right-\left\frac{6}{x^{2}-81}\right$

Factoring the terms $x^{2}-9 x$ and $x^{2}-81$, we get,

$\frac{9}{x(x-9)}-\frac{6}{(x+9)(x-9)}$

Taking LCM, we get,

$\frac{9(x+9)-6x}{x(x-9)(x+9)}}$

Simplifying the numerator, we get,

$\frac{9x+81-6x}{x(x-9)(x+9)}}$

Subtracting the numerator, we have,

$\frac{3 x+81}{x(x-9)(x+9)}$

Hence, the difference is $\frac{3 x+81}{x(x-9)(x+9)}$

7 0
3 years ago
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