![]() Where ŷ is the predicted value, b is the intercept, and m is the slope of the line. Note the method discussed in this blog can as well be applied to multivariate linear regression model. A simple linear regression model used for determining the value of the response variable, ŷ, can be represented as the following equation. Where yi is the actual value, ŷi is the predicted value. In mathematical terms, this can be written as: The residual can be defined as the difference between the actual value and the predicted value. The method relies on minimizing the sum of squared residuals between the actual and predicted values. ![]() ![]() The ordinary least squares (OLS) method can be defined as a linear regression technique that is used to estimate the unknown parameters in a model. What is the ordinary least squares (OLS) method?
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