# Coefficient

## Definition of Coefficient

A coefficient is a number that measures how much one variable changes when another variable changes.

## What is Coefficient used for?

Coefficient is a measure used to quantify the relative strength of a linear relationship between two variables. It can be used to identify how closely related two variables are in a given data set. Coefficients can range from -1 to +1, with 0 indicating no linear correlation between the two variables. A positive coefficient indicates a positive, or direct, correlation; that is, as one variable increases, so does the other. Conversely, when the coefficient is negative, there is an inverse correlation; that is, as one variable increases, the other decreases.

Coefficient values can be interpreted as measures of association which aid in understanding relationships between variables. A value close to 0 suggests very weak linear relationships between two variables and it may be necessary to explore alternative models that better reflect these observed patterns. If a coefficient value is close to 1 (or -1) then this indicates strong linear relationships between the two variables and it could indicate that there may be some underlying mechanism causing them to behave similarly on average across different observations.

In machine learning and data science applications, coefficients are used for model building and regression analysis in order to determine which predictors have the most influence on an outcome variable. They are also often used for feature selection to reduce overfitting by simplifying complex models with lots of parameters or high-dimensional datasets with many features. By calculating coefficients for each feature in the dataset, they can be ranked and those with lower values can be removed from the model without sacrificing too much predictive power or accuracy.