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Two Variable Data
| Term | Definition |
|---|---|
| extrapolating | making predictions |
| LSRL (Least Squares Regression Line) | a unique line that has the smallest possible value for the sum of the squares of the residuals |
| Residual | actual value - predicted value |
| Positive Residual | means that the actual value is greater than the predicted value |
| Negative Residual | the actual value is less than the predicted value |
| residual plot | helps determine if a linear model is a good fit for a scatterplot of data |
| correlation coefficient | r - is a measure of how much or how little data is scattered around the LSRL |
| lurking variable | variable not included in study |
| quadratic model | u shape |
| R^2 Sentence | R^2 percent of the variablity in the dependent variable can be explained by a linear model with the independent variable |
| exponential model | uses exponents |