Seminar Announced: Visual Introduction to Experimental Design Using Diagrams and Excel Exercises

The IR Institute of Engineering Education will host a public seminar designed for those who struggle with statistics, covering the basics of Experimental Design (DOE) through two-way Analysis of Variance (ANOVA). The program emphasizes Excel-based analysis and interpretation of results using visual diagrams.

While Experimental Design is crucial in product and process design, the heavy use of mathematical formulas in statistics often becomes a barrier for learners. Even though software handles the calculations, a conceptual understanding of what those formulas represent is essential for correct interpretation. This seminar provides a step-by-step learning opportunity using visual aids.

### Seminar Overview
- **Title:** Visual Introduction to Experimental Design with Diagrams and Exercises
- **Format:** Online (Live Stream / Archived Stream)
- **Dates:**
- [Live Stream] July 1, 2026 (Wed) 10:00–16:30
- [Archived Stream] July 3 – July 17, 2026
- **Fee:** 49,500 JPY (tax included) per person (Group discounts available)
- **Lecturer:** Akihisa Fukuda (Representative, Stat Imaging Lab)

### Program Highlights
1. **Statistical Basics:** Quantification of variation (standard deviation), standard error, and 95% confidence intervals.
2. **Testing and Estimation of Mean Differences:** Two-group comparison, Excel analysis methods, t-test mechanics, p-values, etc.
3. **One-Way ANOVA:** Methods using Excel, estimation of level means and differences, and relationship with t-tests.
4. **Two-Way ANOVA:** Randomization to prevent confounding, graphing, Excel interpretation, interaction effects, and response surfaces.
5. **Orthogonal Arrays:** Necessity and benefits, usage, structure, assignment, and analysis using general linear models.

### Targeted Audience
- Professionals in product or process design wanting to learn DOE from the ground up.
- Those interested in statistically clarifying cause-and-effect relationships, including in social sciences.

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