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3 years ago

Write the name of a shape that when reflected in the x-axis , will remain identical

Mathematics

2 answers:

olga55 [171]3 years ago

8 0

A circle is one shape that can be reflected
Hope this helps :)

abruzzese [7]3 years ago

5 0

A Reflection is a transformation that does not change the shape or size of any object. It creates a mirror image of the same object at equal distance on the opposite side of line of reflection.

We can list regular objects like Equilateral Triangles, Squares, Regular Pentagon, Regular Hexagon, Regular Octagon, Regular Decagon, and Circles etc.

All these regular objects remain identical after reflection across x-axis.

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Enter the value of p so that the expression 3(4+n) is equivalent to 3(n+p)

Ainat [17]

12 + 3n = 3n + 3p
12 = 3p
Solution: p = 4

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3 years ago

What is -18x - x = 5x -6 PLEASE ANSWER CORRECTLY IT IS MY HOMEWORK

uysha [10]

Answer:

$\large\boxed{x=\dfrac{1}{4}}$

Step-by-step explanation:

$-18x-x=5x-6\\\\-19x=5x-6\qquad\text{subtract}\ 5x\ \text{from both sides}\\\\-19x-5x=5x-5x-6\\\\-24x=-6\qquad\text{divide both sides by (-24)}\\\\\dfrac{-24x}{-24}=\dfrac{-6}{-24}\\\\x=\dfrac{6:6}{24:6}\\\\x=\dfrac{1}{4}$

7 0

3 years ago

What is the number real positive?

san4es73 [151]

Real positive numbers are decimal numbers, not limited to integers, which are above zero.

4 0

3 years ago

Consider the given data. x 0 2 4 6 9 11 12 15 17 19 y 5 6 7 6 9 8 8 10 12 12 Use the least-squares regression to fit a straight

levacccp [35]

Answer:

See below

Step-by-step explanation:

By using the table 1 attached (See Table 1 attached)

We can perform all the calculations to express both, y as a function of x or x as a function of y.

Let's make first the line relating y as a function of x.

y as a function of x

(y=response variable, x=explanatory variable)

$\bf y=m_{yx}x+b_{yx}$

where

$\bf m_{yx}$ is the slope of the line

$\bf b_{yx}$ is the y-intercept

In this case we use these formulas:

$\bf m_{yx}=\frac{(\sum y)(\sum x)^2-(\sum x)(\sum xy)}{n\sum x^2-(\sum x)^2}$

$\bf b_{yx}=\frac{n\sum xy-(\sum x)(\sum y)}{n(\sum x^2)-(\sum x)^2}$

n = 10 is the number of observations taken (pairs x,y)

Note: Be careful not to confuse

$\bf \sum x^2$ with $\bf (\sum x)^2$

Performing our calculations we get:

$\bf m_{yx}=\frac{(83)(95)^2-(95)(923)}{10*1277-(95)^2}=176.6061$

$\bf b_{yx}=\frac{10*923-(95)(83)}{10(1277)-(95)^2}=0.3591$

So the equation of the line that relates y as a function of x is

In order to compute the standard error $\bf S_{yx}$ , we must use Table 2 (See Table 2 attached) and use the definition

$\bf s_{yx}=\sqrt{\frac{(y-y_{est})^2}{n}}$

and we have that standard error when y is a function of x is

$\bf s_{yx}=\sqrt{\frac{39515985}{10}}=1987.8628$

Now, to find the line that relates x as a function of y, we simply switch the roles of x and y in the formulas.

So now we have:

x as a function of y

(x=response variable, y=explanatory variable)

$\bf x=m_{xy}y+b_{xy}$

where

$\bf m_{xy}$ is the slope of the line

$\bf b_{xy}$ is the x-intercept

In this case we use these formulas:

$\bf m_{xy}=\frac{(\sum x)(\sum y)^2-(\sum y)(\sum xy)}{n\sum y^2-(\sum y)^2}$

$\bf b_{xy}=\frac{n\sum xy-(\sum x)(\sum y)}{n(\sum y^2)-(\sum y)^2}$

n = 10 is the number of observations taken (pairs x,y)

Note: Be careful not to confuse

$\bf \sum y^2$ with $\bf (\sum y)^2$

Remark: If you wanted to draw this line in the classical style (the independent variable on the horizontal axis), you would have to swap the axis X and Y)

Computing our values, we get

$\bf m_{xy}=\frac{(95)(83)^2-(83)(923)}{10*743-(83)^2}=1068.1072$

$\bf b_{xy}=\frac{10*923-(95)(83)}{10(743)-(83)^2}=2.4861$

and the line that relates x as a function of y is

To find the standard error $\bf S_{xy}$ we use Table 3 (See Table 3 attached) and the formula

$\bf s_{xy}=\sqrt{\frac{(x-x_{est})^2}{n}}$

and we have that standard error when y is a function of x is

$\bf s_{xy}=\sqrt{\frac{846507757}{10}}=9200.5856$

In both cases the correlation coefficient r is the same and it can be computed with the formula:

$\bf r=\frac{\sum xy}{\sqrt{(\sum x^2)(\sum y^2)}}$

Remark: This formula for r is only true if we assume the correlation is linear. The formula does not hold for other kind of correlations like parabolic, exponential,..., etc.

Computing the correlation coefficient :

$\bf r=\frac{923}{\sqrt{(1277)(743)}}=0.9478$

5 0

4 years ago

Can I get help on this question?

erastova [34]

Answer:

the answer should be 200

4 0

3 years ago

Read 2 more answers