Imagine that you are a research assistant that was asked to summarize the observed associations between FEV (forced respiratory flow) and each of the predictors in the data using SAS. The data are described below. You were given an outline of tables (see below) that you are supposed to fill in(Attached is filled out table). Questions: (1) Based on the table, which predictor has the smallest sum of residuals squared? Which model has the highest sum of residuals squared? (2) Which model should we use if we want to obtain the most accurate estimates of FEV? (3) Why is SSY the same for all the predictors?
Imagine that you are a research assistant that was asked to summarize the observed associations between FEV (forced respiratory flow) and each of the predictors in the data using SAS. The data are described below. You were given an outline of tables (see below) that you are supposed to fill in(Attached is filled out table). Questions: (1) Based on the table, which predictor has the smallest sum of residuals squared? Which model has the highest sum of residuals squared? (2) Which model should we use if we want to obtain the most accurate estimates of FEV? (3) Why is SSY the same for all the predictors?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
Imagine that you are a research assistant that was asked to summarize the observed associations between FEV (forced respiratory flow) and each of the predictors in the data using SAS. The data are described below. You were given an outline of tables (see below) that you are supposed to fill in(Attached is filled out table). Questions: (1) Based on the table, which predictor has the smallest sum of residuals squared? Which model has the highest sum of residuals squared? (2) Which model should we use if we want to obtain the most accurate estimates of FEV? (3) Why is SSY the same for all the predictors?
Transcribed Image Text:a) Using SAS, fill in the following table:
+
Name of the
predictor
SST
Age
1.29868
Height
4.32015
Bone Mass 0.00102
Weight
5.38671
SSE
36.07683
33.05536
37.37449
31.98880
SSY
37.37551
37.37551
37.37551
37.37551
F test statistics
1.69
6.14
0.00
7.91
R²
0.0347
0.1156
0.0000
0.1441
0
Expert Solution
Step 1
The summary data table for predictors is given as-
| Age | 1.29868 | 36.07683 | 37.37551 | 1.69 | 0.0347 |
| Height | 4.32015 | 33.05536 | 37.37551 | 6.14 | 0.1156 |
| Bone Mass | 0.00102 | 37.37449 | 37.37551 | 0 | 0 |
| Weight | 5.38671 | 31.988 | 37.37551 | 7.91 | 0.1441 |
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