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Partial Least SquaresPredicted Response Tables - Confidence Interval |
Minitab displays a confidence interval for each predicted response, providing a range within which you can expect the estimated mean response to fall.
Example Output |
Predicted Response for New Observations Using Model for Moisture 1 14.5184 0.388841 (13.7343, 15.3026) (12.5910, 16.4459) 2 9.3049 0.372712 ( 8.5532, 10.0565) ( 7.3904, 11.2193) 3 14.1790 0.504606 (13.1614, 15.1966) (12.1454, 16.2127) 4 16.4477 0.559704 (15.3189, 17.5764) (14.3562, 18.5391) 5 15.1872 0.358044 (14.4652, 15.9093) (13.2842, 17.0903) 6 9.4639 0.485613 ( 8.4846, 10.4433) ( 7.4492, 11.4787) Test R-sq: 0.906451
Predicted Response for New Observations Using Model for Fat 1 18.7372 0.378459 (17.9740, 19.5004) (16.8612, 20.6132) 2 15.3782 0.362762 (14.6466, 16.1098) (13.5149, 17.2415) 3 20.7838 0.491134 (19.7933, 21.7743) (18.8044, 22.7632) 4 14.3684 0.544761 (13.2698, 15.4670) (12.3328, 16.4040) 5 16.6016 0.348485 (15.8988, 17.3044) (14.7494, 18.4538) 6 20.7471 0.472648 (19.7939, 21.7003) (18.7861, 22.7080) Test R-sq: 0.762701 |
Interpretation |
In this example, the scientists requested a 95% confidence interval. They can be 95% confident that, for the first sample, for all observations with that set of predictor values, the mean response for moisture will be between 13.7343 and 15.3026.