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lara [203]
4 years ago
12

Write the rule for finding the coordinates of a point that has undergone a dilation (with the origin as the point of dilation).

Use this rule to find the coordinates of this point’s dilation from the origin, with a scale factor of : (4, 10).
Mathematics
2 answers:
Talja [164]4 years ago
6 0
The rule for dilation (scale factor k) about the origin is given by:
(x,y)->(kx,ky)
For the point P(4,10)
the image is therefore
P(4,10)->P'(4k,10k)     [ since k is not numerically given ]
When k is known numerically, substitute k into P' to find the numerical coordinates.
Xelga [282]4 years ago
4 0

Answer:

Point (4,10) goes by a dilation of factor m or 1/2 ( With origin as a point of Dilation)=[4 m,  10 m] [4 × 1/2, 10× 1/2]⇒[2,5].

Step-by-step explanation:

Suppose a point has coordinate (x,y).

1.The meaning of Dilation  of a point is  moving to a new point which is at larger distance from origin if we are Dilating by a value i.e an integer in Coordinate System

2. Or If we are Dilating by a fraction which lies between 0<x<1, then distance from origin decreases.

Now , the point (x,y) goes through a Dilation by a factor m(with the origin as point of dilation) , Then New Coordinate of the point= [ m x, my]

Earlier , Distance from origin=x² + y²

Now,Distance from Origin= m² [x² + y²]

If point (4,10) goes through a dilation by factor m ( with the origin as point of dilation)

         =(4 m  ,10 m)

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According to an NRF survey conducted by BIGresearch, the average family spends about $237 on electronics (computers, cell phones
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Answer:

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is 0.0537.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is 0.0023.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is 0.1101.

Step-by-step explanation:

We are given that according to an NRF survey conducted by BIG research, the average family spends about $237 on electronics in back-to-college spending per student.

Suppose back-to-college family spending on electronics is normally distributed with a standard deviation of $54.

Let X = <u><em>back-to-college family spending on electronics</em></u>

SO, X ~ Normal(\mu=237,\sigma^{2} =54^{2})

The z score probability distribution for normal distribution is given by;

                                 Z  =  \frac{X-\mu}{\sigma}  ~ N(0,1)

where, \mu = population mean family spending = $237

           \sigma = standard deviation = $54

(a) Probability that a family of a returning college student spend less than $150 on back-to-college electronics is = P(X < $150)

        P(X < $150) = P( \frac{X-\mu}{\sigma} < \frac{150-237}{54} ) = P(Z < -1.61) = 1 - P(Z \leq 1.61)

                                                             = 1 - 0.9463 = <u>0.0537</u>

The above probability is calculated by looking at the value of x = 1.61 in the z table which has an area of 0.9463.

(b) Probability that a family of a returning college student spend more than $390 on back-to-college electronics is = P(X > $390)

        P(X > $390) = P( \frac{X-\mu}{\sigma} > \frac{390-237}{54} ) = P(Z > 2.83) = 1 - P(Z \leq 2.83)

                                                             = 1 - 0.9977 = <u>0.0023</u>

The above probability is calculated by looking at the value of x = 2.83 in the z table which has an area of 0.9977.

(c) Probability that a family of a returning college student spend between $120 and $175 on back-to-college electronics is given by = P($120 < X < $175)

     P($120 < X < $175) = P(X < $175) - P(X \leq $120)

     P(X < $175) = P( \frac{X-\mu}{\sigma} < \frac{175-237}{54} ) = P(Z < -1.15) = 1 - P(Z \leq 1.15)

                                                         = 1 - 0.8749 = 0.1251

     P(X < $120) = P( \frac{X-\mu}{\sigma} < \frac{120-237}{54} ) = P(Z < -2.17) = 1 - P(Z \leq 2.17)

                                                         = 1 - 0.9850 = 0.015

The above probability is calculated by looking at the value of x = 1.15 and x = 2.17 in the z table which has an area of 0.8749 and 0.9850 respectively.

Therefore, P($120 < X < $175) = 0.1251 - 0.015 = <u>0.1101</u>

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