Answer and step-by-step explanation:
I believe it is 287. I am not entirely sure, but I believe that is the answer.
Minimizing the sum of the squared deviations around the line is called Least square estimation.
It is given that the sum of squares is around the line.
Least squares estimations minimize the sum of squared deviations around the estimated regression function. It is between observed data, on the one hand, and their expected values on the other. This is called least squares estimation because it gives the least value for the sum of squared errors. Finding the best estimates of the coefficients is often called “fitting” the model to the data, or sometimes “learning” or “training” the model.
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Answer:
<em>The equation of the straight line in point - slope form</em>
<em>y +1 = -2 ( x-2)</em>
Step-by-step explanation:
<u><em>Step(i):-</em></u>
Given points are C( 2,-1) and D(1,1)
Slope of the line
m = -2
<u>Step(ii):-</u>
Equation of the straight line passing through the point ( 2,-1) and having slope
m =-2
y - y₁ = m ( x- x₁)
y - (-1) = -2 ( x-2)
y +1 = -2 ( x-2)
<u><em>Final answer:-</em></u>
<em>The equation of the straight line</em>
<em>y +1 = -2 ( x-2)</em>
Answer:
33 miles per 1 gallon
Step-by-step explanation:
