Enter your data for Partial Least Squares Regression

Stat > Regression > Partial Least Squares

Complete the following steps to specify the columns of data that you want to analyze.

  1. In Responses, enter one or more columns of numeric data that you want to explain or predict. PLS fits multiple response variables in a single model. Because PLS models the responses in a multivariate way, the results may differ significantly from those calculated for the responses individually. Model multiple responses separately only if they are uncorrelated.
  2. In Model, enter the columns of numeric data that may explain or predict changes in the response. You can include continuous or categorical variables. You can also specify interaction and polynomial terms. For more information, go to Specifying the model terms in PLS.
  3. In Categorical predictors (optional), enter the categorical classifications or group assignments, such as a type of raw material, that may explain or predict changes in the response.
  4. (Optional) In Maximum number of components, enter the number of components that Minitab calculates or cross-validates. By default, Minitab calculates or cross-validates 10 components or the number of predictors, whichever is less. Do not enter more components than there are terms in the model.
In this worksheet, Strength and Thickness are responses and measure the tensile strength and thickness of blown film. Die temp, Cool temp, Flow, and Extrusion rate are the predictor variables in the model.
C1 C2 C3 C4 C5 C6
Strength Thickness Die temp Cool temp Flow Extrusion rate
8.93 4.62 150.1 80.1 1.0 10.0
8.44 3.70 134.5 49.7 5.0 -10.0
9.72 4.88 179.5 79.8 4.9 10.0
9.55 5.06 149.8 50.3 1.1 10.0
By using this site you agree to the use of cookies for analytics and personalized content.  Read our policy