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Assessment of application of different model selection approaches in multiple regression.
Metadata
Multiple linear regression - decide which variable to exclude
by 
Newcastle University Mathematics and Statistics
-
England schools
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England university
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Scotland schools
Taxonomy: mathcentre
Taxonomy: Kind of activity
Taxonomy: Context
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From users who are members of Stats :
Mario Orsi
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said | Ready to use | 5 years, 1 month ago |
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Mario Orsi 5 years, 1 month ago
Gave some feedback: Ready to use
Mario Orsi 5 years, 1 month ago
Published this.
Mario Orsi 5 years, 1 month ago
Created this as a copy of Multiple linear regression - decide which variable to exclude.| Name | Status | Author | Last Modified | |
|---|---|---|---|---|
| Multiple linear regression - decide which variable to exclude | draft | Newcastle University Mathematics and Statistics | 20/11/2019 14:51 | |
| Multiple linear regression - decide which variable to exclude | draft | Lauren Frances Desoysa | 08/08/2018 10:32 | |
| Multiple linear regression | draft | Lauren Frances Desoysa | 09/08/2018 11:04 | |
| Multiple linear regression - model selection | Ready to use | Mario Orsi | 31/03/2020 22:23 |
There are 2 other versions that do you not have access to.
| Name | Type | Generated Value |
|---|
| p2 | number |
0.18
|
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| p3 | number |
0.13
|
||||
| p0 | number |
0.11
|
||||
| p1 | number |
0.09
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||||
| p4 | number |
0.1
|
||||
| mm | list |
[ 0, 1, 0, 0 ]
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| m | number |
0.18
|
||||
| p | list |
[ 0.09, 0.18, 0.13, 0.1 ]
|
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| v | number |
2
|
||||
| data | list |
Nested 4×2 list
|
||||
| pMax | number |
0.18
|
||||
| R2full | number |
0.21
|
||||
| dataBE | list |
Nested 4×2 list
|
||||
| R2BE1 | number |
0.81
|
||||
| R2BE2 | number |
0.51
|
||||
| R2BE3 | number |
0.88
|
||||
| R2BE4 | number |
0.24
|
||||
| R2BEMax | number |
0.88
|
||||
| dataFS | list |
Nested 4×2 list
|
||||
| R2FS1 | number |
0.31
|
||||
| R2FS2 | number |
0.2
|
||||
| R2FS3 | number |
0.16
|
||||
| R2FS4 | number |
0.04
|
||||
| R2FSMax | number |
0.31
|
||||
| dataFSp | list |
Nested 4×2 list
|
||||
| p1FS | number |
0.04
|
||||
| p2FS | number |
0.16
|
||||
| p3FS | number |
0.14
|
||||
| p4FS | number |
0.03
|
||||
| pMin | number |
0.03
|
Generated value: number
- p0
- p1
- data
- p
- p3
- p3FS
- p4
- p4FS
- pMax
This variable doesn't seem to be used anywhere.
Gap-fill
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The full model is fitted to some data using a statistics software, obtaining R2 adj$=\var{R2full}$.
Four models are then fitted, each excluding a different predictor, obtaining the following output:
R2 adj $=$
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This question is used in the following exams: