R-SquaredThe strength of a linear regression line is determined by the value of the R-squared. If this value is found to be 0, what does it imply?The fitted line explains all the variance in the data.The fitted line explains most of the variance in the data.The fitted line does not explain any variance in the data.The value of the R-squared cannot be zero.

Which statement about the coefficient of determination (R^2) is true?It represents the slope of the regression line.It indicates the percentage of the variance in the dependent variable that is predictable from the independent variable.It can take on any value between -1 and 1.It is the square root of the correlation coefficient.

Which of the following is true of the R-squared (R2) value in Excel's Trendline function? Group of answer choicesA value of 1.0 for R2 indicates maximum deviation of the data from the line.If the value of R2 is above 1.0, the line will be at a perfect fit for the data.The value of R2 will always be between -1 and 1.As the value of R2 gets higher, the line will be a better fit for the data.

When conducting a regression analysis, what does the coefficient of determination (R-squared) represent?  A. The strength of the relationship between variables  B. The predicted values of the dependent variable  C. The slope of the regression line  D. The proportion of variance in the dependent variable explained by the independent variable

What do all the least-squares fit lines have in common?When r = 0, there is no correlation in the data. This means that the value of y doesnot seem to be at all related to the value of x

How does the value of r relate to how easy it is to estimate the least-squares fit line?