Linear regression
Linear Regression
Linear regression (/ˈlaɪnɪər rɪˈɡrɛʃən/) is a statistical method used in the fields of medicine, biology, psychology, economics, and many others. It is a predictive analysis technique that studies the relationship between two or more variables.
Etymology
The term "linear regression" is derived from the field of statistics. "Linear" refers to the relationship between the variables being a straight line, and "regression" refers to the method of predicting a dependent variable based on the values of independent variables.
Definition
Linear regression is a statistical approach for modelling the relationship between a dependent variable, often denoted by Y, and one or more independent variables denoted X. The case of one independent variable is called simple linear regression; for more than one, the process is called multiple linear regression.
Usage in Medicine
In medicine, linear regression is often used to identify the relationships between different biological variables. For example, it can be used to predict the progression of a disease based on certain risk factors, or to understand the relationship between dosage and effect in pharmacology.
Related Terms
- Correlation: A statistical measure that describes the association between random variables.
- Coefficient: A measure of the relationship between the dependent variable and each of the independent variables in regression analysis.
- Residuals: The difference between the observed value of the dependent variable and the predicted value from the regression equation.
- Least squares: The method used in linear regression to find the best-fitting line through the data points.
See Also
External links
- Medical encyclopedia article on Linear regression
- Wikipedia's article - Linear regression
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