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

    … in revenue, and when I spent 2x, I got 1.5x in revenue,” and you should be able to determine a model which best fits how your program reacts with the ad spend using regression analysis. This type of approach works pretty well in a stable market, i.e,. when there isn’t much volatility or any unusual market trends. Anyway, you can look at your weekly click…

    Benjamin Vigneron/ Marketing Landin Paid Search Google How To's- 12 readers -
Get the top posts daily into your mailbox!