Let's take a look at the reports that the Assistant provides. The Assistant takes our candidate X variables and produces a regression model using stepwise regression. We’ll also have the Assistant help us check for interaction effects and curvature.Ĭlick the Optimize Response button and fill in the dialog that appears with this information: From my previous post, we’ve determined that we want to target the heat flux value of 234, but the Assistant can also maximize or minimize the response.

Our response variable is HeatFlux and the X variables are the East, South, and North focal points. Following the tree takes us to Optimize Response at the bottom right. We have three X variables (predictors) and want to fit a regression model and to optimize the response variable. You can click the diamonds for more information about how to choose and for examples of the analyses. In Minitab, go to Assistant > Regression, and you’ll see the interactive decision tree. It now includes an additional variable to highlight the Assistant’s capabilities. I’ve used this example dataset for a previous post about prediction intervals. We’ll use the new features in the Assistant to correctly position the focal points.

They found that heat flux can be predicted by the position of the focal points. In this post, I’ll work through a multiple regression analysis example and optimize the response variable to highlight the new features in the Assistant.Īs part of a solar energy test, researchers measured the total heat flux. Previously, I’ve written about the new linear model features in Minitab 17. If you’re feeling a bit rusty with choosing and using a particular analysis, the Assistant is your friend!

In Minitab, the Assistant menu is your interactive guide to choosing the right tool, analyzing data correctly, and interpreting the results.

Multiple regression in minitab express