17.1 Split-Prediction Methodology
 17.2 Normally Distributed Response Binomial Predictor
  17.2.1 Univariate Case
  17.2.2 Multivariate Case
 17.3 Normally Distributed Response Continuous-Ordinal Predictor
 17.4 Normally Distributed Response Categorical Predictor
 17.5 Linear Regression From a Tree Node
 17.6 Linear Regression with Continuous Response (Optional Module)
  17.6.1 Methodology
  17.6.2 Stepwise Regression
 17.7 Permutation Test Methodology (Optional Module)
 17.8 Results from Linear Regression (Optional Module)
  17.8.1 Residual Spreadsheet
  17.8.2 Linear Regression Statistical Output Viewer
  17.8.3 Overall Statistics
  17.8.4 Regressor Statistics
  17.8.5 Left-Out Regressors
  17.8.6 Parameters
 17.9 Binomially Distributed Response Binary Predictor
  17.9.1 Univariate Case
  17.9.2 Multivariate Case
 17.10 Binomially Distributed Response Continuous/Ordinal Predictor
 17.11 Binomially Distributed Response Categorical Predictor
 17.12 Logistic Regression From a Tree Node
 17.13 Logistic Regression with Binomial Response (Optional Module)
  17.13.1 Methodology
  17.13.2 Stepwise Regression
 17.14 Results from Logistic Regression (Optional Module)
  17.14.1 Residual Spreadsheet
  17.14.2 Logistic Regression Statistical Output Viewer
  17.14.3 Overall Statistics
  17.14.4 Regressor Statistics
  17.14.5 Left-Out Regressors
  17.14.6 Parameters
 17.15 Caveats
 17.16 Categorical Response
 17.17 The False Discovery Rate and the Simes Method
  17.17.1 The False Discovery Rate
  17.17.2 Simes’ Method