Linear Regression Bias

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A Linear Regression Bias is a coefficient of the linear regression function that is a constant term that corresponds to the point that intercepts from the x-origin.



References

2018

2017a

2017b

2009

  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Simple_linear_regression
    • Given a sample [math]\displaystyle{ (Y_i, X_i), \, i = 1, \ldots, n }[/math], the regression model is given by
      • [math]\displaystyle{ Y_i = a + bX_i + \varepsilon_i }[/math]
    • Where [math]\displaystyle{ Y_i }[/math] is the dependent variable, [math]\displaystyle{ a }[/math] is the [math]\displaystyle{ y }[/math] intercept, [math]\displaystyle{ b }[/math] is the gradient or slope of the line, [math]\displaystyle{ X_i }[/math] is independent variable and [math]\displaystyle{ \varepsilon_i }[/math] is a random term associated with each observation.
    • The linear relationship between the two variables (i.e. dependent and independent) can be measured using a correlation coefficient e.g. the Pearson Product Moment Correlation Coefficient.