Answer:
d -13-4i
Step-by-step explanation:
January February March April May June
Acutal 120 140 150 140 150 130
Predicted 80 150 110 150 110 150
Residual 40 −10 40 −10 40 −20
Analyze the data. Determine whether the equation that produced the predicted values represents a good line of best fit.
No, the equation is not a good fit because the residuals are all far from zero.
No, the equation is not a good fit because the sum of the residuals is a large number.
Yes, the equation is a good fit because the residuals are not all far from zero.
Yes, the equation is a good fit because the sum of the residuals is a small number.
The equation that produced these predicted values is not a good fit given that the sum of the residuals is a large number.
The sum of the residuals in a regression is a value that is always supposed to be almost equal to zero in a regression analysis.
The residual tells us that the error term has been reduced to the minimum in the regression analysis.
Read more on a regression analysis here:
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To solve the problem, we apply the properties of a triangle and make a system of linear equations. Setting up appropriate mathematical expressions for angles and solving the equation gives the angles as 30, 80 and 70 degrees.
This problem involves angles in a triangle and can be solved through linear equations. We know from the problem that the largest angle is 20 degrees more than twice the smallest angle, and 5 times the smallest angle equals the sum of the measures of the other two angles.
Solution verification:
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45°
36°
30°
the answer is
d=30 degrees