A least squares regression line: a. may be used to predict a value of y if the corresponding x value is given b. implies a cause-effect relationship between x and y c. can only be determined if a good linear relationship exists between x and y d. None of these alternatives is correct.

a) May be used to predict a value of y if the corresponding x value is given

Step-by-step explanation:

In regression analysis, the vertical distance from the regression line to the data points can be minimized using the least square regression line.

Given the example of a least square regression equation:

y = ax + b

Where

a = slope

b = Y-intercept

If the value of x is known, the value of y may be predicted.

Option A is correct.

A least squares regression line may be used to predict a value of y if the corresponding x value is given

-3

step-by-step explanation:

a drawing really does here:

so i draw the horizontal line y=2 and the vertical line x=-2 at this intersection i put b (this is where my right angle is going to be).   so point b is at (-2,2).   point a is 5 units long and is also on y=2 so this point has to be (3,2) or (-7,2) -doesn't matter i will go with (3,2).

now we know c is at (-2,y) we don't know the y yet bet we know that c is on x=-2.

we have the area of the triangle is .5bh=12.5

we know the base length is 5 (ab)

we have the height is (2-y) if you look at your

plug in

.5(5)(2-y)=12.5

solve for y to get the y-coordinate for c

2.5(2-y)=12.5

divide both sides by 2.5 giving:

2-y=5

now subtract 2 on both sides

-y=3

y=-3