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The regression equation and the standard error of estimate The following scores represent the decrease in symptom intensity (on a 10-point scale) following the new nutrition therapy.

Scores | ||
---|---|---|

Patient | Depression (X) | Pain (Y) |

A | 1 | 5 |

B | 3 | 0.75 |

C | 5 | 7 |

D | 7 | 2.75 |

E | 9 | 9 |

1. Calculate the sum of the products and the sum of squares for X. SP = ________ and SSX = ________

2. Find the regression line for predicting Y given X. The slope of the regression line is ________ and the Y intercept is ________

3. Calculate the Pearson correlation coefficient, the predicted variability, and the unpredicted variability. The Pearson correlation is r = ________ . The predicted variability is SSregression = ________ . The unpredicted variability is SSresidual = ________ .

4. Calculate the standard error of the estimate. The standard error of the estimate is ________ .

5. Suppose you want to predict the pain score for a new patient. The only information given is that this new patient is similar to patients A through E; therefore, your best guess for the new patient's level of pain is ________ . The error associated with this guess (that is, the "standard" amount your guess will be away from the true value) is ________ .

6. Suppose that now you are told the depression score for this new patient is 5.5. Now your best guess for the new patient's level of pain is ________ . The error associated with this guess (that is, the "standard" amount your guess will be away from the true value) is .

7. Finally, suppose before estimating the regression equation, you first transform each of the original scores into a z-score. The regression equation you estimate is: ________

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Answered by MagistrateMusic10854 on coursehero.com

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