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Data Mining and Predictive Modeling
Course Materials
This page provides course materials for teaching data mining and predictive modeling. Additional materials for teaching regression analysis and modeling can be found here.
Statistics, Data Mining and Predictive Modeling with JMP
See a complete listing of JMP capabilities for statistics, data mining and predictive modeling.
Contact the JMP Academic Team.
One Page Guides and Short How-To Videos
Correlation and Regression
- Correlation: Video, guide
- Simple Linear Regression: Video, guide
- Multiple Linear Regression: Video, guide
- Simple Logistic Regression: Video, guide
- Multiple Logistic Regression: Video, guide
- Stepwise Regression: Video, guide
Multivariate Methods
- Clustering: Video, guide
- Principal Components Analysis: Video, guide
- Factor Analysis: Video, guide
- Discriminant Analysis: Video, guide
Data Mining
- Classification Trees (Partition): Video, guide
- Regression Trees (Partition): Video, guide
- Neural Networks: Video, guide
- Creating a Validation Column (Holdout Sample): Video, guide
The complete collection of guides and videos can be found at the JMP Learning Library.
Case Studies
From the Business Case Library
- Cell Phone Service Case Study - Multiple Regression
- Housing Prices Case Study - Multiple Regression
- Lost Sales Case Study - Logistic Regression
From the Analytics Case Library
- Bank Revenues Case - Multiple Regression
- Titanic Passengers Case - Logistic Regression
- Credit Card Marketing Case - Classification Trees
- Customer Churn Case - Neural Networks
- Boston Housing Case - Model Validation and Comparison
The complete collection of case studies is available in the JMP Case Study Library.
JMP Scripts and Add-Ins
Teaching Scripts
Collection: Data Mining Tools Add-Ins
- This is a collection of add-ins used for data mining and predictive modeling, including add-ins for setting the random seed and changing the cutoff value for classification for a confusion matrix.
Additional scripts for teaching data analysis and modeling can be found on the JMP User Community or in the JMP Sample Scripts directory - go to Help > Sample Data, then click on the Open the Sample Scripts button.
Webinare
- Webinar: JMP Basics for Professors and Students
- Webinar: Data Summary and Analysis
- Webinar: Data Visualization and Modeling
- Webinar: Data Preparation and Modeling
- Webinar: Teaching Predictive Modeling with JMP Pro
The completed collection of recorded videos can be found in the Academic Webinar Library. The JMP journals and datasets used in the webinare are also provided.
Books and Book Resources
- Building Better Models with JMP Pro Textbook Page
- Data Mining for Business Analytics Textbook Page
- Fundamentals of Predictive Analytics with JMP®, 2E
- A Practical Guide to Data Mining for Business and Industry
A complete listing of books with JMP can be found here.
Course Materials from the JMP Education Team at SAS*
- JMP Software: Data Exploration (Classic)
- A Case Study Approach to Data Exploration
- ANOVA and Regression
- Introduction to Categorical Data Analysis
- Analyzing Multidimensional Data
- Modeling Multidimensional Data
- Predictive Modeling with JMP Pro
*Complementary materials available to qualified instructors for academic course use. The complete listing of courses is here. To request a set of teaching materials, complete this form.
e-Learning Courses and Instructor Provided Materials
JMP e-Learning Courses
*Complementary materials available to qualified instructors for academic course use. The complete collection of complementary e-learning courses can be found here.
Instructor Provided Materials
Advanced modeling - Generalized Regression (Lasso, Elastic Net, and Ridge):
Other Information for Teaching and Using JMP
Documentation and Help
- Online help: jmp.com/help
- In JMP, Help > Books or Help > JMP Help
Sample Data, Scripts and Add-Ins
- In JMP: Help > Sample Data Library or Help > Sample Data
- Online: JMP User Community File Exchange
Live and Recorded Webinare
- Live Webinare: jmp.com/webcasts
- Recorded Webinare: jmp.com/ondemand
