Data Statistics and Analysis / データ統計解析学

講師 / Lecturer

Prof. OKAMOTO Shogo (Dept. Computer Science)

概要 / Outline of the course

The substantial challenges of real-world systems lie in their involvement with a large number of interrelated factors that deviate statistically. Multivariate analysis and statistics are common tools used to understand and model these complex systems. This course is designed for those who have had limited opportunities to study statistics, multivariate analysis, and the mathematical foundations of these fields. We will cover intermediate topics in classical multivariate analysis and related statistical methods. Throughout the course, we will also practice applying each method of multivariate analysis to real data and interpreting the results.

Topics to be covered.

  • Multiple regression analysis / 重回帰分析
  • Outlier analysis / 外れ値解析
  • Principal component analysis / 主成分分析
  • Factor analysis / 因子分析
  • Discriminat analysis / 判別分析
  • Structural equation modeling / 構造方程式モデリング
  • Covariance selection / 共分散選択
  • Final presentations & discussions by all students

    • 優秀学生 / Student awardees

    全学生は3回のプレゼンテーション形式のレポートを提出し，その内容に基づいてオンライン・プレゼンテーションを実施します． プレゼンテーションは学生間で審査し，5名の学生がファイナル・プレゼンテーション候補者として選出されます． 講義最終日にファイナル・プレゼンテーションを実施し，そこから2名を岡本が優秀学生として選出し，表彰しています． Through three reports and final presentations on data analyses, we identify outstanding students and award certificates.

    Awardees in year 2022 (among 28 students)

  • M. Azechi
  • Y. Nishidamari

    • Awardees in year 2021 (among 40 students, Nagoya University)

  • K. Otake
  • M. Aoki