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cupoosta [38]
3 years ago
14

Bonus question ! If you answer something dumb I'll report you .

Mathematics
2 answers:
Liono4ka [1.6K]3 years ago
4 0
Hello,
We know that
1/Angle 1= Angle 6= Angle 9= Angle 14=Angle 3= Angle 8= Angle 11= Angle 16

2/Angle 2= Angle 5= Angle 10= Angle 13= Angle 4=Angle 7=Angle 12= Angle 15

Check:
Option A:
Angle 2= Angle 7
Parallel
Option B:
Angle 3= Angle 11
Parallel

Option C:
Angle 1= Angle 12
None

Option D:
Angle 13= Angle 12
Parallel

Option E:
Angle 6 angle 7 are supplementary; supplementary means that both angles add up together to get 180°. To help you understand clearly, you see that when the two angle on the same line like angle 5 and 6, angle 1 and 5. However, for this one it will be False because both angle are obtuse which more than 90°. Hope it help!
irinina [24]3 years ago
4 0

Answer:

Option E:

Angle 6 angle 7 are supplementary; supplementary means that both angles add up together to get 180°. To help you understand clearly, you see that when the two angle on the same line like angle 5 and 6, angle 1 and 5. However, for this one it will be False because both angle are obtuse which more than 90°. Hope it help

Step-by-step explanation:

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HELP ASAP Calculate the residuals for your scatterplot in step 2d.
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The residuals of the linear regression equation are -1.36, 0.32, 0.01, 0.62, 0.17, -0.24, 0.89, 0.09, 0.18 and -0.7

<h3>How to determine the residuals?</h3>

The regression equation is given as:

y = 0.141x + 0.842

Next, we calculate the predicted values (y) at the corresponding x values.

So, we have:

y = 0.141 * 13.8 + 0.842 = 2.78

y = 0.141 * 18 + 0.842 = 3.38

y = 0.141 * 16.7 + 0.842 = 3.20

y = 0.141 * 18 + 0.842 = 3.38

y = 0.141 * 0.7 + 0.842 = 0.94

y = 0.141 * 21.9 + 0.842 = 3.93

y = 0.141 * 15.5 + 0.842 = 3.03

y = 0.141 * 9.2 + 0.842 = 2.14

y = 0.141 * 19.5 + 0.842 = 3.59

y = 0.141 * 16.7 + 0.842 = 3.20

The residuals are then calculated using:

Residual = Actual value - Predicted value

So, we have:

Residual = 1.42 - 2.78 = -1.36

Residual = 3.7 - 3.38 = 0.32

Residual = 3.21 - 3.20 = 0.01

Residual = 4 - 3.38 = 0.62

Residual = 1.11 - 0.94 = 0.17

Residual = 3.69 - 3.93 = -0.24

Residual = 3.92 - 3.03 = 0.89

Residual = 2.23 - 2.14 = 0.09

Residual = 3.77 - 3.59 = 0.18

Residual = 2.5 - 3.20 = -0.7

Hence, the residuals of the linear regression equation are -1.36, 0.32, 0.01, 0.62, 0.17, -0.24, 0.89, 0.09, 0.18 and -0.7

Read more about residuals at:

brainly.com/question/16180255

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