# Page 4 - News tagged with statistical model

## AI learns complex gene-disease patterns

Artificial intelligence (AI) is being harnessed by researchers to track down genes that cause disease. A KAUST team is taking a creative, combined deep learning approach that uses data from multiple sources to teach algorithms ...

## Engineers improve the technology of high-performance concrete casting in winter

At low temperatures, concrete tends to set unevenly, which can lead to a collapse. A team of engineers from RUDN University suggested using infrared light and adding silicon and ash to concrete to solve this issue. The technology ...

## Using AI to improve energy and resource efficiency in various industries

The power of machine learning in enhancing the quality of the manufacturing process is getting increasingly recognized. AI and machine learning have become popular tools for manufacturers to improve throughput and optimize ...

## Algorithms help to find minimum energy paths and saddle points more effectively

Olli-Pekka Koistinen, doctoral candidate at Aalto University, developed machine-learning algorithms based on Gaussian process regression to enhance searches of minimum energy paths and saddle points, and tested how well the ...

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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