Level: Intermediate
【Presenter】
Motohisa Hirono, HC Business Headquarters with Business Promotion Center, Ricoh Co., Ltd.
[Announcement summary]
If you use JMP (Pro), you can enjoy analysis more easily than R, Python, etc. It is not a fully custom-made analysis, but it is fully compatible with semi-orders. With JMP, you can easily do the following:
(1) Analysis is possible with one mouse without typing commands, (2) Graph and statistic set, (3) Analysis process can be left in the script, (4) Report can be output according to the flow of the analysis process, (5) Statistical It is ideal for systematic understanding and learning because it is based on various ideas. In this report, we will talk about predictions and classifications that can be done with JMP using numerical examples. The methods to handle are kernel smoothing, SVM and neuro discrimination. In addition, we will deepen our understanding by comparing it with conventional statistical multivariate analysis.
[Presenter Profile]
Joined Ricoh Co., Ltd. in 1984. Since then, he has been engaged in in-house quality management and reliability management work, and enlightenment and dissemination of statistics. After working as the director of the QM Promotion Office of the Quality Headquarters and the director of the SF Business Center, he is in his current position. Tokyo University of Science Faculty of Engineering (1997-1998), Keio University Faculty of Policy Management Part-time Lecturer (2000-2004). His main specialties are statistical quality control and reliability engineering. Major works include "Practice of Graphical Modeling", "How to Use Multivariate Data with JMP", "23 Statistical Calculation Methods Learned from Anscombe's Numerical Examples", "Multivariate Analysis for Engineers with JMP", There is "multivariate analysis of scales from the eyes".
* There are no handouts.
