広島大学シラバス

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年度 開講部局 講義コード 2024年度 先進理工系科学研究科博士課程前期先進理工系科学専攻理工学融合プログラム WSQN2701 専門的教育科目 Data Analytics for Sustainable Development Data Analytics for Sustainable Development 力石　真,鹿嶋　小緒里,保坂　哲朗,李　漢洙 チカライシ　マコト,カシマ　サオリ,ホサカ　テツロウ,リー　ハンスウ 東広島 1年次生   後期   ４ターム (4T) 火1-4：東図書館3Fセミナー室A,東図書館3Fセミナー室B,東図書館3Fセミナー室C 講義 講義中心、演習中心、板書多用、ディスカッション、学生の発表、野外実習、作業、薬品使用 2.0 E : 英語 5 : 大学院基礎的レベル 25 : 理工学 10 : 総合工学 Master Students Data Analysis, sustainable development, interdisciplinary studies (rooted in urban and transportation planning, epidemiology, ecology, climatology) This course is designed for understanding basic statistics and introducing data analytic skills with R for sustainable development studies, including urban and transportation planning, epidemiology, ecology, and climatology. After basic introductory classes on statistics with exercises, four case studies on different disciplines will follow, including advanced methods used in each research field. 1-2. Introduction and descriptive statistics (+exercise)3. Statistical tests (+exercise)4. Statistical tests (+exercise)5. Linear regression (+exercise)6. Linear regression (+exercise)7. Logistic regression (+exercise)8. Logistic regression (+exercise)9. Case 1: Estimation of treatment effects (+exercise)10. Case 1: Estimation of treatment effects (+exercise)11. Case 2: Count data model: Poisson model and its extensions (+exercise)12. Case 2: Count data model: Poisson model and its extensions (+exercise)13. Case 3: Discrete choice model: multinomial logit model and its extensions (+exercise)14. Case 3: Discrete choice model: multinomial logit model and its extensions (+exercise)15. Case 4: Time series analysis: ARMA model and its extensions (+exercise)16. Case 4: Time series analysis: ARMA model and its extensions (+exercise)The maximum number of students for this course is 30. Crawley, M.J. (2014) Statistics: An Introduction Using R, Second Edition, Wiley. (翻訳版：野間口健太郎・菊池泰樹 (2016) 統計学：Rを用いた入門書, 第2版, 共立出版)Dalgaard, P. (2008) Introductory Statistics with R, Springer. R (https://www.r-project.org/) All lectures will be made with exercises in R. Students are required to prepare a PC capable of running R. The maximum number of students for this course is 30. A higher priority will be given to the students who belong to the Transdisciplinary Science and Engineering (TSE) Program. our exercises (5% for each)Four reports (one report for each case. 20% for each) すべての授業科目において，授業改善アンケートを実施していますので，回答に協力してください。回答に対しては教員からコメントを入力しており，今後の改善につなげていきます。
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