Informatics using experimental data that includes variability and outliers: Utilizing data to guide the next experiment.
Materials Informatics (MI) is becoming an important element of digital transformation in research and development, as a method to accelerate and enhance materials development through data utilization.
However, in actual research settings, there are many cases where the introduction of MI stagnates or is abandoned due to reasons such as "the variability of experimental data is large, and I don't know how to utilize it for analysis" or "I don't know how to handle outliers."
In this webinar, we will explain how to confront the "uncertainty of data," which includes variability and outliers, and how to leverage it for decision-making in research and development, along with practical approaches.
Additionally, rather than making the improvement of predictive accuracy the goal itself, we will also introduce perspectives on how to extract "valid insights for the next experiment" from incomplete data, along with specific examples.

| Date and time | Wednesday, Apr 15, 2026 03:00 PM ~ 04:00 PM |
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| Entry fee | Free |
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