Diseases, Conditions, Syndromes

Calculating the beginnings of the coronavirus epidemic

Analyses of publicly available genome data provide clues to the beginnings of the coronavirus epidemic in China. Researchers from the Department of Biosystems Science and Engineering at ETH Zurich in Basel used a statistical ...

Other

Food scientists create zinc index for human body

Zinc deficiency is prevalent around the world, and among children, these mineral shortfalls can lead to stunting, embryonic malformations and neurobehavioral abnormalities. Over several decades, science has improved understanding ...

Diseases, Conditions, Syndromes

Urgently needed: New way to combat vaccine-derived poliovirus

A team of researchers from the U.K., Switzerland, the U.S., and the Congo has found that there is an urgent need to combat a vaccine-derived poliovirus. In their paper published in the journal Science, the group describes ...

Psychology & Psychiatry

How picking up your smartphone could reveal your identity

The time a person spends on different smartphone apps is enough to identify them from a larger group in more than one in three cases say researchers, who warn of the implications for security and privacy.

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Statistical model

A statistical model is a set of mathematical equations which describe the behavior of an object of study in terms of random variables and their associated probability distributions. If the model has only one equation it is called a single-equation model, whereas if it has more than one equation, it is known as a multiple-equation model.

In mathematical terms, a statistical model is frequently thought of as a pair (Y,P) where Y is the set of possible observations and P the set of possible probability distributions on Y. It is assumed that there is a distinct element of P which generates the observed data. Statistical inference enables us to make statements about which element(s) of this set are likely to be the true one.

Three notions are sufficient to describe all statistical models.

One of the most basic models is the simple linear regression model which assumes a relationship between two random variables Y and X. For instance, one may want to linearly explain child mortality in a given country by its GDP. This is a statistical model because the relationship need not to be perfect and the model includes a disturbance term which accounts for other effects on child mortality other than GDP.

As a second example, Bayes theorem in its raw form may be intractable, but assuming a general model H allows it to become

which may be easier. Models can also be compared using measures such as Bayes factors or mean square error.

This text uses material from Wikipedia, licensed under CC BY-SA