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VikaD [51]
3 years ago
12

You are making a scaledrawing of a room using a scale of1 inch : 4 feet.a. The room is 14 feet by 18 feet. Find itsdimensions in

the drawing.b. A sofa in the room has a length of 6 feet.Find the length of the sofa in thedrawing.c. You want to enlarge the scale drawing.How would you change the scale todouble the dimensions of the drawing?Explain.
Mathematics
1 answer:
lilavasa [31]3 years ago
6 0

Answer:

a. 3.5 inches by 4.5 inches

b. 1.5 inches

c. Divide 48 inches by 2 and multiply 1 inch by 12 to get a scale of 1 : 2

Step-by-step explanation:

A scale is a representative fraction showing the relationship between length on a drawing and actual length.

i.e scale = \frac{length on a drawing}{actual length}

 scale = 1 inch : 4 feet

a. The dimensions in the drawing can be determined as;

1 inch : 4 feet implies an inch on the drawing equates 4 feet on actual length.

\frac{14}{4} = 3.5 inches

\frac{18}{4} = 4.5 inches

Dimensions on drawing is 3.5 inches by 4.5 inches.

b. The length of the sofa is 6 feet, its length on the drawing is;

\frac{6}{4} = 1.5 inches

c. To enlarge the scale so as to double the dimensions of the drawing, we have;

12 inches = 1 feet

4 feet = 4 × 12 = 48 inches

given scale = 1 inch : 48 inches

Thus, divide 48 inches by 2 and multiply 1 inch by 12.

scale = 12 inch : 24 inch

scale = 1 : 2

To double the dimensions of the drawing, the scale required is 1 : 2. This implies that a unit measure on the drawing is synonymous to 2 measures on the actual reading.

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Step-by-step explanation:

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Answer:

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Step-by-step explanation:

The mean of geometric distribution is given as , $\mu = \frac{1}{p}$

And the variance is given by, $\sigma ^2=\frac{q}{p^2}$

Given : $p=\frac{1}{1000}$

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The formulae of mean and variance are :

$\mu = \frac{1}{p}$

$\sigma ^2=\frac{q}{p^2}$

$\sigma ^2=\frac{1-p}{p^2}$

a). Mean =   $\mu = \frac{1}{p}$

              = $\mu = \frac{1}{0.001}$

              = 1000

  Variance =   $\sigma ^2=\frac{1-p}{p^2}$

                  = $\sigma ^2=\frac{1-0.001}{0.001^2}$

                           = 999,000

   The standard deviation is determined by the root of the variance.

    $\sigma = \sqrt{\sigma^2}$

        = $\sqrt{999,000}$ = 999.4999

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$\mu=\Sigma\ x\ P(x)= 499 \times 0.001+(-1) \times (1-0.001)$

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