Neuroscience

Optimal evidence accumulation in decision-making

(Medical Xpress)—At the same settings and light conditions, a camera will take the same picture every time. In contrast, a brain does not make perfect reconstructions of a stimulus. It appears instead to accumulate evidence ...

Genetics

New tool reveals the impact of 'jumping genes' on diseases

RIKEN geneticists have developed a tool that can quickly and accurately analyze variants in mobile genetic elements, commonly known as "jumping genes." This promises to shed light on the role such variants play in disease.

Oncology & Cancer

New model predicts 10-year breast cancer risk

A team of researchers at the University of Oxford, led by the Nuffield Department of Primary Care Health Sciences, have developed a new model that reliably predicts a woman's likelihood of developing and then dying of breast ...

Health informatics

A global overview of antibiotic resistance determinants

To understand the main determinants behind worldwide antibiotic resistance dynamics, scientists from the Institut Pasteur, Inserm, Université de Versailles Saint-Quentin-en-Yvelines and Université Paris-Saclay developed ...

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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