Explain how to predict y-values using the equation of a regression line. A. Substitute a value of y into the equation of a regression line and solve for x. B. Use the graph of the regression line to determine the x-value that corresponds to the y-value for which you are solving. C. Substitute a value of x into the equation of a regression line and solve for y^.D. Substitute the correlation coefficient into the equation and solve for y^

C. Substitute a value of x into the equation of a regression line and solve for y

Step-by-step explanation: To predict y values using equation of the regression line, a given value of x is substituted into the equation as there are only two unknowns in the whole regression equation, which are the x value ( independent variable) and the y value (the dependent or predicted variable).

The regression equation is usually of the form:

y = mx + c (linear regression)

Where y = predicted or dependent variable

m = slope or gradient of the regression line

x = independent variable

c = intercept of the line (where it cross the y-axis)

the data of the detroit pistons in numerical order from least to greatest is 0.30, 0.37, 0.55, 0.62, 0.69, 0.72, 0.73, 0.75, 0.77, 0.78, 0.80, 0.81, 0.81, 0.83, 0.84, 0.89

the data of the miami heat in numerical order from least to greatest is 0.50, 0.50, 0.56, 0.57, 0.67, 0.72, 0.72, 0.72, 0.75, 0.75, 0.76, 0.81, 0.82, 0.90, 1.00, 1.00

the detroit pistons median : 1.52

the miami heat median: 1.47

the iqr of this data is 0.05