Easy peasy
just subsitute I(x) for the x in the h(x) so
h(I(s))=-(2s+3)^2-4
distribute and simplify
h(I(s))=-(4s^2+12s+9)-4
h(I(s))=-4s^2-12s-9-4
h(I(s))=-4s^2-12s-13
A plot of residuals (vertical deviations from the regression line) shows the errors or lack of fit, so it would indicate a good fit if the residuals are small, vs. over fit if they are large. Due to age related growth short pre teen, and a plateau after age 21, I would expect a linear regression would offer estimate age 5.5 years.
Answer:
4x + 4y - 8
Step-by-step explanation:
4(x - 2 +y) = 4*x -4*2 + 4*y by the distributive property
Answer:
x + y = 84
Step-by-step explanation:
Given
x : y : z = 5 : 1 : 3, then
= 5 ( multiply both sides by y )
x = 5y ←
and 
= 
( cross- multiply )
3y = z
Substitute z = 3y into z - y = 28
3y - y = 28
2y = 28 ( divide both sides by 2 )
y = 14 ← ←
Substitute y = 14 into x = 5y
x = 5 × 14 = 70 ← ←
Substitute y = 14 into z - y = 28
z - 14 = 28 ( add 14 to both sides )
z = 42 ← ←
Thus x = 70, y = 14 and z = 42
Hence x + y = 70 + 14 = 84
You just have to multiply 17.04 * 6.2 to get the answer. The answer is 105.648
