Advanced Data Science Techniques in SPSS

Advanced Data Science Techniques in SPSS

Advanced Data Science Techniques in SPSS

Hone your SPSS skills to perfection – grasp the most high level data analysis methods available in the SPSS program.

What you’ll learn

• Perform advanced linear regression using predictor selection techniques
• Perform any type of nonlinear regression analysis
• Make predictions using the k nearest neighbor (KNN) technique
• Use binary (CART) trees for prediction (both regression and classification trees)
• Use non-binary (CHAID) trees for prediction (both regression and classification trees)
• Build and train a multilayer perceptron (MLP)
• Build and train a radial basis funcion (RBF) neural network
• Perform a two-way cluster analysis
• Run a survival analysis using the Kaplan-Meier method
• Run a survival analysis using the Cox regression
• Validate the predictive techniques (KNN, trees, neural networks) using the validation set approach and the cross-validation
• Save a predictive analysis model and use it for predictions on future new data

Requirements

• SPSS program installed (version 21+)
• Basic SPSS knowledge
• Basic or intermediate statistics knowledge

Who this course is for:

• students
• PhD candidates
• academic researchers
• business researchers
• University teachers
• anyone who is passionate about data analysis and data science

ENROLL NOW