Statistical Analysis Software JMP: Learning Data Analysis for Engineers through "Trial & Error" - Practical Exploration of Factors and Building Predictive Models
This seminar is aimed at engineers primarily in the manufacturing industry, focusing on data utilization, and will explain practical approaches to factor exploration and predictive model building.
1. What to do before the model: Key points for data preparation and trial & error using JMP
We will introduce the necessary preprocessing and feature creation required before analysis.
- Understanding the contents of the data (visualization and summary statistics)
- Dealing with missing values and outliers
- Creating variables to enhance model accuracy (feature engineering)
- Tips for efficiently progressing the creation of analysis data
2. How to proceed with factor exploration and predictive model building without making it a black box
Based on the data prepared in the first half, we will explain the process of factor exploration and predictive model building.
- Visualization of factors using correlation analysis, regression models, and decision trees
- Model evaluation using training and validation data
- Comparison and selection of multiple machine learning models (e.g., neural networks, random forests, etc.)
- Intuitive understanding of important factors and prediction results
▼ Details & Registration
https://www.jmp.com/ja/events/seminars/non-series/2026/06-19-factor

| Date and time | Friday, Jun 19, 2026 02:00 PM ~ 04:00 PM The event will be held in person. There are no plans for a hybrid format or archive streaming. |
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| Capital | SAS Institute Japan Co., Ltd. Tokyo Headquarters 11th Floor, Roppongi Hills Mori Tower, 6-10-1 Roppongi, Minato-ku, Tokyo Nearest station: Toei Subway / Tokyo Metro "Roppongi" |
| Entry fee | Free Advance registration is required. |
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