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Nat2105 [25]
3 years ago
10

6x9x(-5) what is the answer to this question?

Mathematics
1 answer:
9966 [12]3 years ago
7 0
-270. Use the google calculator.
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Step-by-step explanation:

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A rectangle and a square have the same area. a. The width of the rectangle is w inches. The length of the rectangle is 15 inches
harkovskaia [24]

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Answer:

  a) w(4w-15)

  b) w²

  c) w(4w -15) = w²

  d) w = 5

  e) 5 by 5

Step-by-step explanation:

a) If w is the width, and the length is 15 less than 4 times the width, then the length is 4w-15. The area is the product of length and width.

  A = w(4w -15)

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b) If w is the side length, the area of the square is (also) the product of length and width:

  A = w²

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c) Equating the expressions for area, we have ...

  w(4w -15) = w²

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d) we can subtract the right side to get ...

  4w² -15w -w² = 0

  3w(w -5) = 0

This has solutions w=0 and w=5. Only the positive solution is sensible in this problem.

The side length of the square is 5 units.

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e) The rectangle is 5 units wide, and 4(5)-15 = 5 units long.

The rectangle and square have the same width and the same area, so the rectangle must be a square.

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Answer:

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Step-by-step explanation:

It is the only one that increases by 8 just like the pattern

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Answer:

D. No, because the sample size is large enough.

Step-by-step explanation:

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

If the sample size is higher than 30, on this case the answer would be:

D. No, because the sample size is large enough.

And the reason is given by The Central Limit Theorem since states if the individual distribution is normal then the sampling distribution for the sample mean is also normal.

From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

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