Which of the following regressions represents the strongest positive linear relationship between x and y?
Regression 1
y=ax+by=ax+b
a=15.7a=15.7
b=1.7b=1.7
r=1.0278r=1.0278 Regression 2
y=ax+by=ax+b
a=3.5a=3.5
b=0.7b=0.7
r=0.5986r=0.5986 Regression 3
y=ax+by=ax+b
a=7.7a=7.7
b=18.2b=18.2
r=0.4741r=0.4741 Regression 4
y=ax+by=ax+b
a=-17.9a=−17.9
b=-16.2b=−16.2
r=-0.7989r=−0.7989

It is defined as the relation between two variables which is a quantitative type and gives an idea about the direction of these two variables.

We have

Regression 1

y=ax+b where a=15.7, b=1.7, and r=1.0278

Regression 2

y=ax+b where a=3.5, b=0.7, and r=0.5986

Regression 3

y=ax+b where a=7.7, b=18.2 and r=0.4741

Regression 4

y=ax+b where a=-17.9, b=-16.2, and r=-0.7989

Here r is the correlation coefficient.

We know r = 1 represents the perfect positive correlation.

When the value of r is near 1 we can say the correlation is the strongest positive.

From the given data the nearest value of r is 1.0278 from 1.

Regression 1 represents the strongest positive correlation.

Thus, regression 1 represents the strongest positive linear relationship between x and y.

Learn more about the correlation here:

brainly.com/question/11705632