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The quadratic regression equation that best fits the data set is y = 32.86x² - 379.14x + 1369.14
<h3>The data points </h3>The following table of values represents the data points that would be used to solve this question:
x 3 4 5 6 7 8 9
y 470 416 403 226 314 338 693
Where:
- x represents years since 2000
- y represents the annual revenue of a manufacturing company in thousand dollars
The table of values illustrates a quadratic function.
The function would be calculated using a graphing calculator
From the graphing calculator, we have:
a = 32.86; b = -379.14 and c = 1369.14
A quadratic regression equation is represented as:
y = ax² + bx + c
So, we have:
y = 32.86x² - 379.14x + 1369.14
Hence, the quadratic regression equation that best fits the data set is y = 32.86x² - 379.14x + 1369.14
<h3>Why the function type was chosen?</h3>From the table of values in (a), we can see that as x increases; the value of y decreases and then increases after it reaches a minimum.
This illustrates the behavior of a quadratic regression function
See attachment for the scatter plot
Read more about quadratic regression equation at:
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Answer:
Start
A2
B2
B1
C1
C2
D2
D3
D4
C4
END
Step-by-step explanation:
Start (A3)
x is equal to 141 because they are alternate interior angles.
A2. x is equal to 39 because they are corresponding angles.
B2. x would be supplementary to 41 because the angle that x supplements is corresponding to 41.
41 + x = 180 due to the linear pair postulate. Therefore, x = 139.
B1. x would be supplementary to 82 because they are consecutive exterior angles.
82 + x = 180 due to the linear pair postulate. Therefore, x = 98.
C1. x = 102 due to the vertical angles theorem.
C2. x would be supplementary to 130 because the angle that x supplements is equal to 130 (Alternate Exterior Angles).
130 + x = 180, x = 50.
D2. x = 74, corresponding angles.
D3. x = 83, corresponding angles.
D4. x = 95, corresponding
C4. x is supplementary to 18 because of the consecutive interior angles theorem.
x = 162
END
