Carrie and Ryan have both computed the slope of the least-squares line using data for which the standard deviation of the x-values and the standard deviation of the y-values are equal. Carrie gets a value of 0.5 for the slope, and Ryan gets a value of 2. One of them is right. Which one?

Carrie's slope value is correct.

Step-by-step explanation:

The least square regression line is:

Here is the slope of the line.

The formula to compute the slope is:

Here = standard deviation of x and = standard deviation of y.

It is provided that the standard deviation of x and y are equal.

So the slope of the regression line is:

Thus, if the standard deviation of x and y are equal the slope of the line is same as the correlation coefficient.

The correlation coefficient is a measure used to determine the strength of the linear relationship between the variables.

It ranges from -1 to 1.

Carrie's slope value was 0.50 and Ryan's slope value was 2.

Since -1 ≤ r ≤ 1 the value of slope cannot be 2.

Thus, Ryan's slope value is incorrect.

step-by-step explanation:

there is a formula i can give you:

it is r^2*n*sin(360/n) divided by 2 where r represents the "radius" and n is the number of sides.

plug them in:

(10sqrt(3))^2*6*sin(360/6) divided by 2

100*3*6*sin(60) divided by 2

900*sin(60)

900*sqrt(3)/2

450*sqrt(3)

approx is 779.4 cm^2

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happy to

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