Answer: Probably C
Step-by-step explanation:
Answer: There is not a good prediction for the height of the tree when it is 100 years old because the prediction given by the trend line produced by the regression calculator probably is not valid that far in the future.
Step-by-step explanation:
Years since tree was planted (x) - - - - height (y)
2 - - - - 17
3 - - - - 25
5 - - - 42
6 - - - - 47
7 - - - 54
9 - - - 69
Using a regression calculator :
The height of tree can be modeled by the equation : ŷ = 7.36X + 3.08
With y being the predicted variable; 7.36 being the slope and 3.08 as the intercept.
X is the independent variable which is used in calculating the value of y.
Predicted height when years since tree was planted(x) = 100
ŷ = 7.36X + 3.08
ŷ = 7.36(100) + 3.08
y = 736 + 3.08
y = 739.08
Forward prediction of 100 years produced by the trendline would probably give an invalid value because the trendline only models a range of 9 years prediction. However, a linear regression equation isn't the best for making prediction that far in into the future.
Colorado and Boston have 263 and 219 days of sunshine respectively.
<h3>
What is the solution to the Equation?</h3>
Let the number of days of sunshine in Colorado is x and the number of days of sunshine in Boston is y.
Total number of days of sunshine=482
Also, the number of days of sunshine in Colorado is 1.2 times the number of days of sunshine in Boston.
So, the equation is formed as follows:
x+y=482 -(1)
The other equation is formed as:
x=1.2y -(2)
Substitute the value x from equation (2) in (1),
1.2y+y=482
2.2y=482
y=482/2.2
y=219
Substitute the value of y in equation (1),
x+219=482
x=482-219
x=263
Learn more about Equations here:
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Answer:
b
Step-by-step explanation:
because the line i tercept of x is the s sloped
75 divided by 225 is 0.333...
so it would be A