Sike this system of equations by graphing . First graph the equations and then type the solution y=7/2x+3 y=-x-6

Thank you! please help!

zvonat [6]

The answer should be D. Y = -3x

7 0

3 years ago

Read 2 more answers

Triangle sum theorem<br> i will give brainliest

AveGali [126]

Answer:

The answer is b=128

Step-by-step explanation:

25+27=52

180-52=128

6 0

3 years ago

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How many perfect squares lie between 10 and 64 how do you know?

ira [324]

4, (16,25,36,49)

5 including the number 64

5 0

4 years ago

Finding the area of a right triangle

muminat

Formula: A = ab/2 unless you need a fully answer question?

6 0

3 years ago

The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x

Andrew [12]

Answer:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

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:

$r^2 = 0.8^2 = 0.64$

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:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

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:

$r^2 = 0.8^2 = 0.64$

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.

3 0

3 years ago