Answer:
B.) 45
Step-by-step explanation:
The assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
Important assumptions in regression model analysis are
- There should be a linear and additive relationship between dependent (response) variable and independent (predictor) variable(s).
- There should be no correlation between the residual (error) terms. Absence of this phenomenon is known as auto correlation.
- The independent variables should not be correlated. Absence of this phenomenon is known as multi col-linearity.
- The error terms must have constant variance. This phenomenon is known as homoskedasticity. The presence of non-constant variance is referred to heteroskedasticity.
- The error terms must be normally distributed.
Hence we can conclude that the assumptions of a regression model can be evaluated by plotting and analyzing the error terms.
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Answer:
x = 12
Step-by-step explanation:
Step 1: Define
f(x) = 4x + 6
f(x) = 54
Step 2: Substitute variables
54 = 4x + 6
Step 3: Solve for <em>x</em>
<u>Subtract 6 on both sides:</u> 48 = 4x
<u>Divide both sides by 4:</u> 12 = x
Step 4: Check
<em>Plug in x to verify it is a solution.</em>
f(12) = 4(12) + 6
f(12) = 48 + 6
f(12) = 54
Plug 
into the equation of the ellipsoid:
Complete the square:
Then the intersection is such that
which resembles the equation of a circle, and suggests a parameterization is polar-like coordinates. Let
(Attached is a plot of the two surfaces and the intersection; red for the positive root 
, blue for the negative)
