Practical methods of advanced statistics are explained.
To master the gramer of science for your research.
Analysis of variance, Regression analysis, Analysis of interaction. Parameter design, Graphical modeling
|✔ Specialist skills||Intercultural skills||Communication skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
Exercise is performed in every class. PC or EC are necessary.
|Course schedule||Required learning|
|Class 1||Orientation, Buffon needle||Estimation of dintance|
|Class 2||One-way layout: anaysisi of variance and orthogonal polynomial||Application of orthogonal polinomial|
|Class 3||Analysis of three-way contingency table||Application of Mntel and Hentzel Test|
|Class 4||corelation, multiple cprelation, partial corelation||Analysis of partial corelation|
|Class 5||path analysisl||Application of path analysis|
|Class 6||Interaction analysis for two-way data Application of orthogonal polynomial||Application of orthogonal for two-way data|
|Class 7||Interaction analysis for two-way data Application of FANOVA model||Application of FANOVA model|
|Class 8||Principal component analysis||Analysis with principal component analysis|
|Class 9||Correspondence Analysis||Applicatiopn of correspondence analysis|
|Class 10||Multiple correspondence analysis||Application of multiple correspondence analysis|
|Class 11||Analysis of covariance and intermediate variable||Application of analysis of variance|
|Class 12||Metric multi-dimensional scaling||Application of metric multi-dimensional scaling|
|Class 13||Discriminant analysis||Analysis with asymmetric discrimminant analysis|
|Class 14||Graphicak modeling: Covariance selection||Application of covariance selection|
Enkawa,T. and Miyakawa,M. SQC Theoey and Practice
Miyakawa,M. Statistical Technology
Miyakawa,M. Graphical MOdelong
Miyakawa,M. Technology for Getting Quality
Evaluation of reports.
Elementary ｓtatistical methods