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1 vote
-50 POINTS- (2/5) please no wrong answers for points. A) y =
(9)/(2) x +
(1)/(2) B) y = -
(1)/(2) x + (7)/(2) C)
y = -4x +9 D)
y=4x+15

-50 POINTS- (2/5) please no wrong answers for points. A) y = (9)/(2) x + (1)/(2) B-example-1

2 Answers

1 vote

Answer:


\Large \boxed{y=-(1)/(2) x+(7)/(2) }

Explanation:

Using a graph,

we can see that the line y = -1/2x + 7/2 best fits for the data.

-50 POINTS- (2/5) please no wrong answers for points. A) y = (9)/(2) x + (1)/(2) B-example-1
-50 POINTS- (2/5) please no wrong answers for points. A) y = (9)/(2) x + (1)/(2) B-example-2
User Ylan S
by
5.4k points
4 votes

This problem is about creating a linear regression model.

First, we should take note of the points:

(-4,8)

(-2,4)

(-1,2)

(1,5)

(2,2)

(6,-5)

(7,6)

It's necessary to find a equation y = ax + b that brings us the least MSE (Mean Squared Error). You can calculate at hand, but I bet it is going to be tiresome.

So, basically intuitively you just need to choose a line that fits closer to the given points.

First: remember if y = ax+b, a is the slope which means if a > 0 the line is " / " and a < 0 the line is " \ ".

A) No, this equation is " / "

B) It could be this one.

C) It could be this one too.

D) Nope. " / "

B) a = -1/2

C) a = -4

You can draw those two lines and see that B) gets closer to the points.

Equation:

Y = -0.4957*X + 3.780

Answer: B)

User Andre Gregori
by
4.3k points