Terms : Hide Images
| 5795024764 | explanatory variable | may help explain or predict changes in a response variable | 0 | |
| 5795025375 | response variable | measures an outcome of a study | 1 | |
| 5795026007 | scatterplot | shows the relationship between two quantitative variables measured on the same individuals | 2 | |
| 5795028066 | FODS | how to describe a scatterplot by form, outlier, direction, and shape | 3 | |
| 5795032477 | positive association | the association between two variables when above-average values of one tend to accompany above-average values of the other and when the below-average values also tend to occur together | 4 | |
| 5795034069 | negative association | the association between two variables when above-average values of one tend to accompany below-average values of the other | 5 | |
| 5795035652 | Form | describing a scatterplot as a linear or curved pattern | 6 | |
| 5795037807 | Direction | describing a scatterplot as having a positive or negative association | 7 | |
| 5795038519 | Strength | describing a scatterplot based on how tightly the points lie in relationship to the best fit line | 8 | |
| 5795040734 | Outlier | describing a scatterplot that has obvious outliers or other departures from the overall pattern | 9 | |
| 5795042140 | correlation | measures the direction and strength of the linear relationship between two quantitative variables | 10 | |
| 5795043621 | regression line | a line that describes how a response variable y changes as an explanatory variable x changes, used in making predictions | 11 | |
| 5795045155 | y-hat | the predicted value of the response variable y for a given value of the explanatory variable x | 12 | |
| 5795046052 | slope | the amount by which y is predicted to change when x increases by one unit | 13 | |
| 5795048287 | extrapolation | the use of a regression line for prediction far outside the interval of values of the explanatory variable x used to obtain the line, such predictions are not accurate | 14 | |
| 5795049631 | residual | the difference between an observed value of the response variable and the value predicted by the regression line | 15 | |
| 5795050761 | least-squares regression line (LSRL) | the line that makes the sum of the squared residuals as small as possible | 16 | |
| 5795051745 | residual plot | a scatterplot of the residuals against the explanatory variable, helps us assess whether a linear model is appropriate | 17 | |
| 5795053107 | standard deviation of the residuals | this value gives the approximate size of a "typical" prediction error (residual) | 18 | |
| 5795054810 | coefficient of determination | r-squared, the fraction of the variation in the values of y that is accounted for by the LSRL of y on x. | 19 |
