Answer:
The image of point (x , y) by dilation with center origin and scale factor k is (kx , ky)
Step-by-step explanation:
* Lets talk about dilation
- A dilation is a transformation that changes the size of a figure.
- It can become larger or smaller, but the shape of the
figure does not change.
- The scale factor, measures how much larger or smaller
the image will be
- If the scale factor greater than 1, then the image will be larger
- If the scale factor between 0 and 1, then the image will be smaller
* In a problem of dilation
∵ The center of dilation is the origin
∵ The scale factor of dilation is k
∵ The point is (x , y)
- In dilation with center origin and scale factor k to find the image
of the point multiply each coordinates of the point by the scale
factor k because the distance d between the point and the
origin will be equal kd which is the distance between the origin
and the image of the point d is depending on the coordinates
of the point
∴ The image of point (x , y) by dilation with center origin and
scale factor k is (kx , ky)
* Ex: If point A is (3 , 4)
∵ The distance from the origin to point A =
∵ The scale factor of dilation is 2 and the center is the origin
∴ The image of A is A' = (3 × 2 , 4 × 2) = (6 , 8)
∵ The distance from the origin to point A' =
∵ 10 ÷ 5 = 2 which is the value of the scale factor
∴ The image of point (x , y) by dilation with center origin and
scale factor k is (kx , ky)
Answer:
300
Step-by-step explanation:
You take your 3000 and write it down. When you are dividing numbers and fractions, you divide by the bottom and multiply by the top. Following this, we know that 1/10 is equal to divided by 10. You now go back to that paper and look at your 3000. Divided by 10 is just moving the decimal point one to the left. that leaves you with 300.0, or 300.
Answer:
sorry no answer of that man
Step-by-step explanation:
i haerd efan seggy has answer
3 points define a parabola, so the regression will be unique. You want to find a quadratic polynomial such that
where the system above is generated by setting , , and .
Since , we have
So the regression for the given data points is .