| A | B |
|---|
| Functional Relationship | A relationship in which one variable is an exact weighted combination of one or more variableoos or constants |
| Slope | The degree that a regression line rises or falls as one moves along it from left to right |
| Intercept | The point at which the regression line crosses the Y-axis |
| Predicted Value | In regression analysis , the expected value of the dependent variable for a given value of the independent variable based on the calculated regression line |
| Regression | A statistical technique used to describe the relationship between two variables based on the principle of minimizing errors in prediction |
| Least Squares | In regression analysis, the principle of minimizing the sum of squared errofs to fit the regression line to the data |
| Regression Coefficient | The weight assigned to independent variables in a regression |
| Error | In regression analysis, the distance a data point is from the regression line |
| Residual Variation | The avaerage squared error in prediction with a regression equation |
| Standard Error of the Estimate | An estimate of the error in an estimate of Y derived from a regression equation |
| Coefficient of Determination | A measure of goodness of fit for a regression line based on the ratio of explained variation to total variation |
| Correlation Coeffiient | The square root of the coefficient of determination with a plus or minus sign the same as that for the slope |
| Standard Error of the Slope | A measure of goodness of fit in a regression |
