1)A model is linear when each term is either a constant or the product of a parameter and a predictorvariable. A linear equation is constructed by adding the results for each term. This constrains theequation to just one basic form:Response = constant + parameter * predictor + ... + parameter * predictorY = b o + b1X1 + b2X2 + ... + bkXkIn statistics, a regression equation (or function) is linear when it is linear in the parameters. While theequation must be linear in the parameters, you can transform the predictor variables in ways thatproduce curvature. For instance, you can include a ...
To Order an Original Plagiarism Free Paper on the Same Topic Click Here
Other samples, services and questions:
When you use PaperHelp, you save one valuable — TIME
You can spend it for more important things than paper writing.