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Step-by-step explanation:
Answer:
C. 52
Step-by-step explanation:
First, find the base of the triangle. You can do this by looking at the top of the figure. 14 inches is the width of the rectangle, and 20 inches is the width of the rectangle and the base of the triangle. You can find the base of the triangle by subtracting.

The base of the triangle is 6. The height of the triangle is equal to the height of the rectangle, 8. Now you need to find the hypotenuse of the triangle using the Pythagorean theorem:

c is the hypotenuse. Find c:

The hypotenuse of the triangle is 10. Now that you know the hypotenuse, you can find the perimeter. Add all the sides:

The perimeter is 52 inches.
The value of the variable x in the equation –x + 8 + 3x = x – 6 is - 14.
<h3>How to find variable in an equation?</h3>
The variables of an equation can be found as follows:
–x + 8 + 3x = x – 6
The variable in the equation is x.
Therefore,
–x + 8 + 3x = x – 6
combine like terms on the left side
-x + 3x + 8 = x - 6
2x + 8 = x - 6
subtract x form both sides of the equation
2x - x + 8 = - 6
x + 8 = -6
subtract 8 from both sides
x = -6 - 8
x = - 14
learn more on equation here: brainly.com/question/1347990
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Answer:
true
Step-by-step explanation:
Answer:
![r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%28%5Csum%20xy%29-%28%5Csum%20x%29%28%5Csum%20y%29%7D%7B%5Csqrt%7B%5Bn%5Csum%20x%5E2%20-%28%5Csum%20x%29%5E2%5D%5Bn%5Csum%20y%5E2%20-%28%5Csum%20y%29%5E2%5D%7D%7D)
The value of r is always between 
And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

So then the best conclusion for this case would be:
c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.
Step-by-step explanation:
For this case we know that the correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. And we know that we use the height x of a child to predict the weight y of the child
We need to rememeber that the correlation is a measure of dispersion of the data and is given by this formula:
![r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}](https://tex.z-dn.net/?f=r%3D%5Cfrac%7Bn%28%5Csum%20xy%29-%28%5Csum%20x%29%28%5Csum%20y%29%7D%7B%5Csqrt%7B%5Bn%5Csum%20x%5E2%20-%28%5Csum%20x%29%5E2%5D%5Bn%5Csum%20y%5E2%20-%28%5Csum%20y%29%5E2%5D%7D%7D)
The value of r is always between 
And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

So then the best conclusion for this case would be:
c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.