Answer:
No
Step-by-step explanation:
Do they have common factors?
No which is why they are not able to be simplified further
so no
This can happen if you add another independent variable to your regression model that is strongly correlated to some other variable already in the model.
This is called multicollinearity.
If there is a high correlation between your independent variables can lead to problems.
<span>It can lead to increased variance of the coefficient estimates and make the estimates very sensitive to minor changes in the model.</span>
Answer:
x = 5, x = 1
Step-by-step explanation:
The quadratic equation 0 = 4(x - 3)2 - 16.
Using binomial theorem, (a - b)2 = a2 - 2ab + b2 to expand (x - 3)2.
0 = 4(x2 - 6x + 9 ) - 16.
Using distributive property to multiply 4 by x2 - 6x + 9.
0 = 4x2 - 24x + 36 - 16.
Subtract 16 from 36 to get 20.
0 = 4x2 - 24x + 20.
4x2 - 24x + 20 = 0.
Divide both sides by 4.
x2 - 6x + 5 = 0.
To solve the equation, factor and rewrite as x2 + ax + bx + 5
a + b = -6, ab = 1(5) = 5.
a = -5, b = -1.
Rewriting x2 - 6x + 5 as
(x2 - 5x) + (-x + 5)
Factor x in the first and -1 in the second group.
x(x - 5) - (x - 5)
Factor out common term
(x - 5)(x - 1)
By solving the above, we get
x = 5, x = 1