Level: Beginner
【Presenter】
Akira Ogawa, Visiting Researcher, Faculty of Business Administration, Mejiro University
[Presentation summary]
In recent years, the need for rational processing of large amounts of diverse data has increased, and data science has become increasingly important. There are two types of this education: a passive type where students learn knowledge and analytical methods through classroom lectures, and an active type where students learn to solve problems and accomplish tasks through practical exercises. Until now, passive education has been mainly promoted, and substantial results have already been obtained. However, active education is considered to be a future issue, and there is a strong need to develop an approach for it.
In practice, the PDCA cycle approach of planning, doing, checking, and acting has been used for many years to solve problems and accomplish tasks, and has achieved many results. The essence of this is to collect facts in the form of data, analyze them, come up with a hypothesis based on the conclusions obtained, implement it, collect the results as data, and verify the hypothesis. This is active data science itself.
For many years, the authors have developed an educational program that uses both coin shooting materials and the PDCA cycle, and have implemented it in lectures and seminars, and have presented its contents in various venues (papers, conference presentations, lectures, etc.). I have given many presentations. In this presentation, we will systematically organize these and report on active data science education.
[Presenter profile]
After working as an engineer at a measurement and control manufacturer, he earned a doctoral degree in business administration from Mejiro University's Faculty of Business Administration through research on statistical quality control. JMP has been used for data analysis for over 20 years, primarily for experimental design and multivariate data analysis. Data science has been attracting a lot of attention in society in recent years, but based on my experience in data analysis as a former manufacturer, I place emphasis on the actual site, where data is generated. For data cleaning to obtain good data, on-site and actual information is important. This coin shooting teaching material also simulates or reproduces the actual situation. The research theme is to use JMP to perform highly accurate analysis and use it for various improvements and decision-making.
[Co-presenter]
Institute of Statistical Mathematics Takenori Takahashi
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