Single linear regression
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A singleSingle linear regression, also known as a simple linear regression, in statistics, is a technique that maps a relationship between one independent and one dependent variable into a first degree-degree polynomial. Linear regression is the simplest example of curve fitting, a type of mathematical problem in statistics.
Linear regression creates a very limited model because it represents a relationship as a straight line (first degree-degree polynomial). A first degree-degree polynomial can describe various different data distributions without giving insight into the true relationships between the variables, which may be better described by a higher degree polynomial.
Another limitation of the linear regression model is that real world-world problems usually involve multiple variables which affect a dependent variable. In the case that multiple variables affect a dependent variable, a multiple regression analysis is more precise in describing the relationships of the variables.
-<p><strong>A single linear regression</strong>, also known as a simple linear regression, in statistics, is a technique that maps a relationship between one independent and one dependent variable into a first degree polynomial. Linear regression is the simplest example of curve fitting, a type of mathematical problem in statistics.</p><p>Linear regression creates a very limited model because it represents a relationship as a straight line (first degree polynomial). A first degree polynomial can describe various different data distributions without giving insight into the true relationships between the variables, which may be better described by a higher degree polynomial.</p><p>Another limitation of the linear regression model is that real world problems usually involve multiple variables which affect a dependent variable. In the case that multiple variables affect a dependent variable a <a href="/articles/multiple-regression-analysis">multiple regression analysis</a> is more precise in describing the relationships of the variables.</p>- +<p><strong>Single linear regression</strong>, also known as <strong>simple linear regression</strong>, in statistics, is a technique that maps a relationship between one independent and one dependent variable into a first-degree polynomial. Linear regression is the simplest example of curve fitting, a type of mathematical problem in statistics.</p><p>Linear regression creates a very limited model because it represents a relationship as a straight line (first-degree polynomial). A first-degree polynomial can describe various different data distributions without giving insight into the true relationships between the variables, which may be better described by a higher degree polynomial.</p><p>Another limitation of the linear regression model is that real-world problems usually involve multiple variables which affect a dependent variable. In the case that multiple variables affect a dependent variable, a <a href="/articles/multiple-regression-analysis">multiple regression analysis</a> is more precise in describing the relationships of the variables.</p>
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