Common Statistical Models

Dirk P. Kroese and Joshua Chan
Additional contact information
Dirk P. Kroese: The University of Queensland, School of Mathematics and Physics

Chapter Chapter 4 in Statistical Modeling and Computation, 2014, pp 101-120 from Springer

Abstract: Abstract The conceptual framework for statistical modeling and analysis is sketched in Fig. 4.1. The starting point is some real-life problem (reality) and a corresponding set of data. On the basis of the data we wish to say something about the real-life problem. The second step consists of finding a probabilistic model for the data. This model contains what we know about the reality and how the data were obtained. Within the model we carry out our calculations and analysis. This leads to conclusions about the model. Finally, the conclusions about the model are translated into conclusions about the reality.

Keywords: Linear Regression Model; Multiple Linear Regression Model; Multivariate Normal Distribution; Polynomial Regression Model; Nonlinear Regression Model (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-8775-3_4

Ordering information: This item can be ordered from
http://www.springer.com/9781461487753

DOI: 10.1007/978-1-4614-8775-3_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().