Based on the scatterplot and residual plot, what type of model is appropriate for comparing time and subscribers? A linear model is appropriate because the residual plot shows a random scatter of points. A logarithmic model is appropriate because the log of the number of subscribers was taken. A power model is appropriate because the relationship between period and the log of subscribers is roughly linear. An exponential model is appropriate because the relationship between period and the log of subscribers is roughly linear and the residual plot shows no distinct pattern.

answer:   the paragraph proof is mentioned below.

step-by-step explanation:

given: in a δxwy where

such that, ∠wzx ≅ ∠yzx and zw≅zy

we have to prove that: segment zx is a perpendicular bisector of segment wy.

prove: since, zw≅zy ⇒ ∠wzy is a supplementary angle.

then, ∠wzy= 180°

⇒∠wzx + ∠yzx = 180° ( because xz divides ∠wzy into two parts)

but, ∠wzx ≅ ∠yzx ( given)

⇒∠wzy+∠wzy=180° ( by substitution)

⇒2∠wzy=180°

⇒∠wzy=90°

⇒∠wzy=∠yzx =90°

therefore, xz⊥wy where wz=zy

⇒zx is a perpendicular bisector of wy.

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the answer is c.

perimeters = 3√10/5

areas = 90/25

i got it down chief.