Terms : Hide Images
| 11122511625 | Correlation (r) | Measures strength and direction ( + or - ) | 0 | |
| 11122511626 | Words to describe strength | Strong (when r is close to 1 or -1), moderately strong/weak, weak (when r is close to 0) | 1 | |
| 11122511627 | Words to describe direction | Positive, negative | 2 | |
| 11122511628 | Correlation coefficient | r |  | 3 |
| 11122511629 | r is resistant or non-resistant to outliers? | Non-resistant | 4 | |
| 11122511630 | If r=1 | Perfect positive linear slope | 5 | |
| 11122511631 | If r=-1 | Perfect negative linear slope | 6 | |
| 11122511632 | What are the units of r? | r has no units | 7 | |
| 11122511633 | What is the range of r? | -1 < r < 1 | 8 | |
| 11122511634 | Residual | Observed value (y) - predicted value (y "hat") | 9 | |
| 11122511635 | Least squares regression line (LSRL) | The line that makes the sum of the sqaures of the vertical distances of the data points from the line as small as possible. | 10 | |
| 11122511636 | What point is always on the LSRL? | (x¯, y¯ ) | 11 | |
| 11122511643 | Interpretation of the slope of the LSRL | For every one unit increase in ___(x)___ the predicted ___(y)___ increases/decreases on average by ___(b)___ units | 12 | |
| 11122511644 | Coefficient of determination | Is the proportion of the variation in the values of y that is explained by the LSRL | 13 | |
| 11122511645 | r² | Coefficient of determination | 14 | |
| 11122511646 | r² measures... | "how good the LSRL is at predicting y" | 15 | |
| 11122511647 | Interpretation of coefficient of determination | r² % of the variation in ___(y)___ is accounted for by the LSRL | 16 | |
| 11122511650 | The sign of r matches the sign of... | b1 (slope of the LSRL) | 17 | |
| 11122511651 | Residual Plot | helps determine if a linear model is an appropriate model for a data set | 18 | |
| 11122511655 | Outlier | A point that does not follow the pattern of the data and has a large residual. | 19 | |
| 11122511656 | Influential point | any point that substantially changes the slope, y-int, r, r^2, or S | 20 | |
| 11122511659 | Form, direction, and strength (IN CONTEXT) | "Describing the scatterplot" means to discuss the... | 21 | |
| 11122599485 | standard deviation of the residuals | typical prediction error | 22 | |
| 15303527039 | high leverage point | points that have much larger or smaller x-values than the other points in the data set | 23 |
