Answer:
it's answer is y + 185 = 250; y = 65
hope it helps you
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.
Answer:
x and y
Step-by-step explanation:
Answer:

If
is constant, say k
Then,

∴ d ∝ w
Hence, weight is proportional to the density
Step-by-step explanation:
From the question,
Let w denote the weight of the rock in pounds
s denote the size of the rock in cubic inches and
d denote the density of the rock in pounds per cubic inch.
First, we will write the equation connecting w, s, and d.
We get

That is,

Now, given a 48-cubic-inch rock with weight w pounds, to show the proportional relation between the weight and the density, we will write

If
is constant, say k
Then,

∴ d ∝ w
Hence, density is proportional to the weight OR weight is proportional to the density
Ok so obvi you can’t multiply 1/6 so u have to divide top on bottom out so 1 divided by 6 so your awnser would be 2.5