We square the residuals when using the least-squares line method to find the line of best fit because we believe that huge negative residuals (i.e., points well below the line) are just as harmful as large positive residuals (i.e., points that are high above the line).
<h3>What do you mean by Residuals?</h3>
We treat both positive and negative disparities equally by squaring the residual values. We cannot discover a single straight line that concurrently minimizes all residuals. The average (squared) residual value is instead minimized.
We might also take the absolute values of the residuals rather than squaring them. Positive disparities are viewed as just as harmful as negative ones under both strategies.
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Answer:
.25
Step-by-step explanation:
2 eggs are pink
4 eggs are purple
2 eggs are orange
-----------------------
8 total eggs
P( orange) = orange eggs/ total eggs
= 2/8
= 1/4
= .25
Answer:
See below
Step-by-step explanation:
The result of the calculation of area ( L x W ) should have no more significant digits than the lowest factor ....in this case 75 has only TWO significant digits...... the naswer should have the same ...two
75 * 50.3 = ~3800 cm^2
Answer:
Maximize C =


and x ≥ 0, y ≥ 0
Plot the lines on graph




So, boundary points of feasible region are (0,1.7) , (2.125,0) and (0,0)
Substitute the points in Maximize C
At (0,1.7)
Maximize C =
Maximize C =
At (2.125,0)
Maximize C =
Maximize C =
At (0,0)
Maximize C =
Maximize C =
So, Maximum value is attained at (2.125,0)
So, the optimal value of x is 2.125
The optimal value of y is 0
The maximum value of the objective function is 19.125