Hiroshima University Syllabus

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Academic Year School/Graduate School Lecture Code 2022Year School of Informatics and Data Science KA112001 Specialized Education 推測統計学 スイソクトウケイガク Inferential Statistics YANAGIHARA HIROKAZU ヤナギハラ　ヒロカズ Higashi-Hiroshima 2nd-Year,  First Semester,  1Term (1T) Tues5-8：ENG 103 Lecture Lecture-oriented, Note-taking, Teams, Bb9 2.0 B : Japanese／English 2 : Undergraduate Low-Intermediate 25 : Science and Technology 01 : Mathematics/Statistics Random variable, probability distribution, point estimation, interval estimation Informatics and Data Science Program（Knowledge and Understanding）・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.（Abilities and Skills）・A. Skills related to the development of an information infrastructure,information processing techniques, and technology for producing new added value through data analysis.・ B. Ability to identify and solve new problems on their own by quantitative and logical thinking based on data, diverse perspectives, and advanced skills for information processing and analysis. We study elementary inference statistics lesson1 Population and statistical modellesson2 Random variablelesson3 Expectationlesson4 Various probability distributionslesson5 Convergences of random variablelesson6 Point estimationlesson7 Unbiasedness, variance, mean square errorlesson8 Consistencylesson9 Asymptotic normalitylesson10 Least square estimationlesson11 Least square estimation for simple regressionlesson12 Maximum likelihood estimationlesson13 Maximum likelihood estimation under normalitylesson14 Interval estimationlesson15 Interval estimations in various settingsThere might be some small changes on lessons Not specified Hand-out, PC Please do not hesitate to ask a question if you have dubious points You can choose between face-to-face, online, and on-demand lecture formats. You can choose between face-to-face, online, and on-demand lecture formats, but the number of face-to-face participants will be limited to avoid crowding. Tasks and Report Please fill in the class improvement questionnaire which is carried out on all classes.Instructors will reflect on your feedback and utilize the information for improving their teaching.
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