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MrRissso [65]
3 years ago
11

Can somebody help me please

Mathematics
2 answers:
luda_lava [24]3 years ago
5 0

Answer:

800

Step-by-step explanation:

900-100= 800

Therefore, the difference is 800. I hope this helps, have a great day!!!

Strike441 [17]3 years ago
5 0

Answer:

800

Explanation:

When solving this problem we need to remember that it is asking us to find how much money she gained throughout the day, NOT the total amount she had at the end of the day. To find how much money she gained, simply subtract one hundred by nine hundred.

900 - 100

800

Therefore, $800 was the change in how much money she had.

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Step-by-step explanation:

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What is x if x(x+3)(x+3)=0
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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
The points A,B and C lie on a straight line
aev [14]

I think 0 but if I am wrong I'm sorry

Step-by-step explanation:

6 0
2 years ago
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