Updated on 2023/04/14

写真a

 
Hayashi Toshiharu
 
Organization
Graduate School of Informatics Department of Core Informatics Associate Professor
School of Engineering Department of Information Science
Title
Associate Professor
Affiliation
Institute of Informatics
Affiliation campus
Nakamozu Campus

Position

  • Graduate School of Informatics Department of Core Informatics 

    Associate Professor  2022.04 - Now

  • School of Engineering Department of Information Science 

    Associate Professor  2022.04 - Now

Degree

  • 工学博士 ( Others ) (   Osaka University )

Papers

  • Laws of large numbers in self-correcting point processes Reviewed

    Toshiharu Hayashi

    Stochastic Processes and their Applications 雑誌   23 ( 2 )   319 - 326   1986.12

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    Kind of work:Single Work  

Books and Other Publications

  • 理工系の数理 確率・統計

    岩佐 学, 薩摩 順吉, 林 利治( Role: Joint author)

    裳華房  2018.11 

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    Responsible for pages:180  

Charge of on-campus class subject

  • 機械学習構成論

    2022   Weekly class   Graduate school

  • 確率統計学

    2022   Weekly class   Graduate school

  • データ解析

    2022   Weekly class   Undergraduate

  • 情報リテラシー

    2022   Weekly class   Undergraduate

  • 数理・データサイエンス基礎B

    2022   Weekly class   Undergraduate

  • Advanced Intelligent Information Systems I

    2021    

  • Advanced Knowledge Management

    2021    

  • Advanced Machine Learning

    2021    

  • Basic Computer Science (Including Information Society and Ethics)

    2021    

  • Data Analysis

    2021    

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Visiting Lectures ⇒ Link to the list of Visiting Lectures

  • 平均値は平均的か!? 身近な平均のウラの顔に迫ります

    Category:Science (mathematics, physics, chemistry, biology, geology, biochemistry), Engineering (machinery, electronics / physics, electrical / electronics, electrical information, chemical biotechnology, architecture, cities (civil engineering / environment), material chemistry, aerospace, marine systems, applied chemistry, chemistry, materials)

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    Audience:High school students, College students, General

    Keyword:平均値, 統計学 

    データを「代表する」ように計算される「中間的」な値である「平均値」が代表的なのか、中間的なのかをいくつかの例で調べ、身近であったはずの「平均値」のウラの顔に迫ります。