JMP Pro Predictive Modeling

1. Data Exploration: Explore and visualize data to identify patterns and trends.

2. Predictive Modeling: Build predictive models using regression, decision trees, and machine learning algorithms.

3. Model Assessment: Evaluate model performance using cross-validation and other techniques.

4. Variable Selection: Select important variables for modeling using various selection methods.

Before learning JMP Pro Predictive Modeling, it's beneficial to have the following skills:

1. Statistical Analysis: Understanding of basic statistical concepts such as regression, correlation, and hypothesis testing.

2. Data Analysis: Proficiency in data manipulation, exploration, and visualization using tools like Excel, R, or Python.

3. Predictive Modeling Concepts: Familiarity with the principles of predictive modeling, including model building, evaluation, and validation.

4. Data Cleaning: Ability to clean and preprocess data to ensure its quality and suitability for modeling.

By learning JMP Pro Predictive Modeling, you gain the following skills:

1. Data Exploration: Ability to explore and visualize data to identify patterns and trends.

2. Predictive Modeling Techniques: Proficiency in building predictive models using regression, decision trees, and machine learning algorithms.

3. Model Assessment: Skills to evaluate model performance using techniques like cross-validation and ROC analysis.

4. Variable Selection: Knowledge of methods for selecting important variables and features for modeling.