Regression Review In regression, we are trying to build a model to predict Y based on certain predictor variables (x 1, x 2, etc.). Please feel free to leave a comment at the end of this page. So, we will take a look at how stepwise regression can easily build a model for you as well as a few of the drawbacks of stepwise regression. As with all techniques, there are some caveats about using stepwise regression. Sit back and let the model be built for you. On the surface, this technique sounds great. This month’s publication takes a look at stepwise regression. This is an automated process that builds a regression model for you by going through a series of steps of adding the most significant variable or removing the least significant variable. This is where stepwise regression can help. How can you go through these 40 variables to see which ones really impact sales and could become part of a model to predict sales? Well, you could run a full regression analysis with all 40 variables and see which ones are “significant.” But regression models change as variables are added or removed. You have a database that contains 40 different variables that might impact sales. September 2015 You would like to able to predict what sales will be.
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