In statistics, reification is the use of an idealized model of a statistical process. The model is then used to make inferences connecting model results, which imperfectly represent the actual process, with experimental observations.
Also, [1] a process whereby model-derived quantities such as principal components, factors and latent variables are identified, named and treated as if they were directly measurable quantities.
Notes
- ^ Everitt, 2002
References
- Everitt, B.S. (2002) Cambridge Dictionary of Statistics (2nd Edition), CUP. ISBN 0-521-81099-X
 | This statistics-related article is a stub. You can help Wikipedia by expanding it. |
In statistics, reification is the use of an idealized model of a statistical process. The model is then used to make inferences connecting model results, which imperfectly represent the actual process, with experimental observations.
Also, [1] a process whereby model-derived quantities such as principal components, factors and latent variables are identified, named and treated as if they were directly measurable quantities.
Notes
- ^ Everitt, 2002
References
- Everitt, B.S. (2002) Cambridge Dictionary of Statistics (2nd Edition), CUP. ISBN 0-521-81099-X
|
| This statistics-related article is a stub. You can help Wikipedia by expanding it. |