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AP STAT
chpt. 6(scatter, association, correlation) & 7(linear regression)
| Term | Definition |
|---|---|
| Scatter plots show | the relationship between 2 quantitative variables measured on the same cases. |
| Direction (describing association) | positive (increase) or negative (decrease) |
| Form (describing association) | patterns: scatter, mostly linear |
| Strength (describing association) | amount of scatter: weak (lot) or strong (close, clump, or linear) |
| Line of best fit is equal to | least squares line |
| r^2 or R^2 (squared correlation) | gives the fraction of the data's variation accounted for by the model and 1-r^2 is the fraction of the original variation left in the residuals. |
| r^2 is always between | 0% and 100% |
| Correlation coefficient (-1<r>1) and conditions you must check | Quantitative variables conditions: correlation only for quantitative straight enough condition: judgement call No outliers condition: check for them, they effect everything |
| Best fit means | least squares |
| residuals(e)= | observed value (y) - predicted value (y-hat) |
| X and Y variables in scatterplots | x= explanatory y= response |
| Lurking variables | In scatter plots and correlation coefficients never prove causation. A hidden variable that stands behind, a relationship and determines it. |
Created by:
jcore
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