Check all that's TRUE about the "best-fit" line? The line is horizontal when the correlation coefficient is 0 . It is used to predict values that are not in the data. It must contains all scattered points. It makes the least distance from every point. The slope is the correlation coefficient.

1. **The line is horizontal when the correlation coefficient is 0.** When the correlation coefficient \( r=0 \), the slope of the regression line \( b \) is given by \[ b = r\frac{s_y}{s_x} \] so \( b=0 \). Thus, the line is horizontal, showing that there is no linear relation between the variables. **This statement is true.** 2. **It is used to predict values that are not in the data.** The best-fit line (or regression line) is commonly used to predict or estimate the value of the dependent variable for new, unseen values of the independent variable (extrapolation or interpolation). **This statement is true.** 3. **It must contains all scattered points.** There is no requirement that the regression line passes through every data point. It is calculated to minimize the sum of the squares of the vertical differences between the observed values and the fitted values. **This statement is false.** 4. **It makes the least distance from every point.** The regression line is determined by minimizing the sum of the squares of the *vertical distances* (errors) from the data points to the line, not the perpendicular (shortest) distances. **This statement is false.** 5. **The slope is the correlation coefficient.** The slope \( b \) of the best-fit line is given by \[ b = r\frac{s_y}{s_x}, \] where \( s_y \) and \( s_x \) are the standard deviations of the \( y \) and \( x \) values respectively. The slope equals the correlation coefficient only when \( s_y = s_x \); in general, it is not equal to \( r \). **This statement is false.** Thus, the true statements are the first and the second.