Final answer:
The intercept of the regression line represents the value of the dependent variable when all independent variables are zero. It is a crucial point on the y-axis that estimates the dependent variable's value assuming no influence from independent variables. The slope indicates how the dependent variable is expected to change in relation to the independent variable.
Step-by-step explanation:
The intercept of a regression line represents the value of the dependent variable when all independent variables are zero. The correct statement is 1) The intercept represents the value of the dependent variable when all independent variables are zero. This means at the point where the regression line crosses the y-axis, the value shown provides an estimate for the dependent variable if the independent variables were to have the value of zero. In some scenarios, this might not make practical sense, as some variables cannot be zero. For example, it would not be meaningful to find the value of a final exam score (the dependent variable) when the third exam score (the independent variable) is zero, especially if the dataset does not include such cases.
Understanding the slope of a line is crucial as it indicates how the dependent variable changes in response to changes in the independent variable—represented graphically by different types of lines in statistics. A positive slope shows that there is a direct relationship between the two variables; as one increases, so does the other.