Multiple Regression

In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. (This term should be distinguished from multivariate linear regression, where multiple correlated dependent variables are predicted,[citation needed] rather than a single scalar variable.)In linear regression, data are modeled using linear predictor functions, and unknown model parameters are estimated from the data. Such models are called linear models.
Posts about Multiple Regression
  • How To Predict Marginal Returns In Search

    … simulations are not available). I won’t spend too much time explaining how to put together the data, as it is described in my previous post – but, long story short you should be able to put together the below table and yield curve quite easily by aggregating those AdWords’ bid simulations. Note that the two yield curves we have now, one based…

    Benjamin Vigneron/ Marketing Landin Paid Search Google How To's- 13 readers -