It's called the least squares method because the parameters of the regression line are adjusted in such a way that the sum of squares of the difference (between the actual and predicted values) is a minimum.
Answer:
3053.63m³
Step-by-step explanation:
use a calculator, not brainly
The answer is:
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b = y − mx .
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Explanation:
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Given:
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y = mx + b ;
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We want to isolate "b" on one side of the equation to solve for "b".
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→ y = mx + b ; Subtract "mx" from BOTH sides of the equation; to isolate "b" one side of the equation; and solve for "b":
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y = mx + b → y − mx = mx + b − mx ;
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→ y − mx = b ; ↔ b = y − mx
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→ b = y − mx .
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