Immunology

Reducing air pollution could cut rates of childhood asthma

(HealthDay)—Statistical models demonstrate how targeting certain air pollutants could reduce the incidence of childhood asthma, according to a study published online July 22 in the Proceedings of the National Academy of ...

Diseases, Conditions, Syndromes

Harvard undergrad's AI model helps to predict TB resistance

One of the greatest challenges in treating tuberculosis—the top infectious killer worldwide, according to the World Health Organization (WHO)—is the bacterium's ability to shapeshift rapidly and become resistant to multiple ...

Health

Stopwatch set for milestone marathon in 2032

By estimating a statistical model for male and female marathon world record progressions, Dr. Angus also found that 1:58.05 is likely the fastest time that any living human being will be able to run this distance.

Diseases, Conditions, Syndromes

Model for improving campylobacter management

A refined model for understanding the source of campylobacter infections may be a key management tool for public health officials around the world.

Psychology & Psychiatry

Implicit attitudes can change over the long term

Data from more than 4 million tests completed between 2004 and 2016 show that Americans' attitudes toward certain social groups are becoming less biased over time, according to research published in Psychological Science, ...

page 1 from 10

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