An equation was created for the line of best fit from actual enrollment data. it was used to predict the dance studio enrollment values shown in the table below: enrollment month january february march april may june actual 12 14 14 13 16 14 predicted 8 15 15 12 17 15 residual 4 −1 −1 1 −1 −1 analyze the data. determine whether the equation that produced the predicted values represents a good line of best fit. no, the equation is not a good fit because the sum of the residuals is a large number. no, the equation is not a good fit because the residuals are all far from zero. yes, the equation is a good fit because the residuals are all far from zero. yes, the equation is a good fit because the sum of the residuals is a small number.

No, the equation is not a good fit because the sum of the residuals is a large number.

Step-by-step explanation:

A residual is the difference on the scatter plot between the actual y-value and the predicted y-value from the regression line equation.

It is the vertical distance from the actual plotted point to the point on the regression line.

The residual is positive then the data point is above the graph.

The sum of the given residual values =

Since,  the sum of the residuals is greater than 0.

Therefore, The equation is not a good fit .

x = ±sqrt(10)

step-by-step explanation:

5 - 2x² = -15

subtract 5 from each side

5-5 - 2x² = -15-5

-2x^2   = -20

divide by -2 on each side

-2x^2   /-2= -20/-2

x^2 =10

take the square root on each side

sqrt(x^2 )=±sqrt(10)

x = ±sqrt(10)

check:

5 - 2x² = -15

+sqrt(10)

5 - 2(sqrt(10))² = -15

5 -2(10) = -15

5 -20 = -15

-15 = -15

-sqrt(10)

5 - 2(-sqrt(10))² = -15

5 -2(10) = -15

5 -20 = -15

-15 = -15

-2/