X-1%x^2-2x-3 =0
X-1=0
X=1 , ≠-1 , x≠3
Answer X=1
Answer:
B
Step-by-step explanation:
Use formula given above
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.
Hello,
tan 22°=450/d
==>d=450/tan 22°=1113.7890... ≈1114 (ft)
Answer:
141000 * (1 - 0.016)^15 = 110699.48 = A 110700
Step-by-step explanation:
1st year depreciation = 141000 - (141000 * 0.016) = 138744
2nd year depreciation = 138744 - (138744 * 0.016) = 136524.096
3rd year depreciation = 136524.096 - (136524.096 * 0.016) = 134339.710464
etc. unitl you reach the 15th year
Basically we calculate 1.6% of the current value of the house and subtract that from the current value for each year for 15 years.
The equation used in the answer is a faster way to approach your answer instead of calculating for each year.
You'd multiply your initial value by the difference in percentage (note well that since it is decreasing in value we subtract the decimal equivalent to 1.6% which is 0.016, from 1 where one represents 100% and then raise the difference gained to the power of the amount of years which would be 15.