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==== Linear regression ====
{{main|Linear regression}}
In linear regression, a plot is constructed with the previous values of the dependent variable plotted on the Y-axis and the independent variable that is being analyzed plotted on the X-axis. A regression line is then constructed by a statistical program representing the relationship between the independent and dependent variables which can be used to predict values of the dependent variable based only on the independent variable. With the regression line, the program also shows a slope intercept equation for the line which includes an addition for the error term of the regression, where the higher the value of the error term the less precise the regression model is. In order to decrease the value of the error term, other independent variables are introduced to the model, and similar analyses are performed on these independent variables.<ref name=":0" /><ref>{{Cite web |title=Linear Regression |url=http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm |access-date=2022-05-06 |website=www.stat.yale.edu}}</ref> Additionally, multiple linear regression (MLP) can be employed to address relationships involving multiple independent variables, offering a more comprehensive modeling approach.<ref>{{Cite journal |last=Li |first=Meng |last2=Liu |first2=Jiqiang |last3=Yang |first3=Yeping |date=2023-10-14 |title=Financial Data Quality Evaluation Method Based on Multiple Linear Regression |url=https://www.mdpi.com/1999-5903/15/10/338 |journal=Future Internet |language=en |volume=15 |issue=10 |pages=338 |doi=10.3390/fi15100338 |issn=1999-5903|doi-access=free }}</ref>
== Applications ==
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