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散布図と相関 / Scatter Plots and Correlations

Kenji Saito
December 09, 2023

散布図と相関 / Scatter Plots and Correlations

早稲田大学大学院経営管理研究科「企業データ分析」2023 冬のオンデマンド教材 第5回で使用したスライドです。

Kenji Saito

December 09, 2023
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  1. generated by Stable Diffusion XL v1.0
    2023
    5
    (WBS)
    2023 5 — 2023-12 – p.1/16

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  2. https://speakerdeck.com/ks91/collections/corporate-data-analysis-2023-winter
    2023 5 — 2023-12 – p.2/16

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  3. ( 20 )
    1 •
    2 R •
    3 •
    4 •
    5 •
    6 ( )
    7 (1)
    8 (2)
    9 R ( ) (1)
    10 R ( ) (2)
    11 R ( ) (1)
    12 R ( ) (2)
    13 GPT-4
    14 GPT-4
    15 ( ) LaTeX Overleaf
    8 (12/21 ) / (2 ) OK
    /
    2023 5 — 2023-12 – p.3/16

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  4. RStudio Git ( )
    2
    2023 5 — 2023-12 – p.4/16

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  5. RStudio Git ( )
    RStudio Git
    Git
    ( GPL)
    GitHub Git
    ( )
    RStudio
    pull
    2023 5 — 2023-12 – p.5/16

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  6. Git
    RStudio
    Git (OS )
    Linux : ( OK)
    macOS : Xcode (Apple )
    Xcode AppStore
    https://apps.apple.com/jp/app/xcode/id497799835
    Windows : https://gitforwindows.org
    OK
    https://github.com/ks91/cda-demo
    Git
    2023 5 — 2023-12 – p.6/16

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  7. (scatter plot) 2
    x y ( )
    (◦ )
    plot (verb): mark out or allocate (points) on a graph
    cda-demo “ .R”
    1
    2023 5 — 2023-12 – p.7/16

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  8. “ .txt” 1
    1 <- read.table(" .txt", header=T)
    plot( 1, xlim=c(0, 100), ylim=c(0, 100),
    xlab=" ", ylab=" ",
    main=" ")
    :
    2023 5 — 2023-12 – p.8/16

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  9. 0 20 40 60 80 100
    0 20 40 60 80 100
    ṇࡢ┦㛵ࡢ౛
    ⱥㄒࡢヨ㦂⤖ᯝ
    ᩘᏛࡢヨ㦂⤖ᯝ
    2023 5 — 2023-12 – p.9/16

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  10. “ .txt” 2
    2 <- read.table(" .txt", header=T)
    plot( 2, xlim=c(0, 20.0), ylim=c(13.0, 18.0),
    xlab=" ",
    ylab="100m ( )",
    main=" ")
    :
    2023 5 — 2023-12 – p.10/16

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  11. 0 5 10 15 20
    13 14 15 16 17 18
    ㈇ࡢ┦㛵ࡢ౛
    㐌ᙜࡓࡾࡢㄢእ㐠ື᫬㛫
    100m㉮ࡢࢱ࢖࣒ (⛊)
    2023 5 — 2023-12 – p.11/16

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  12. 1 2
    plot( 1$ , 2$ ,
    xlim=c(0, 100), ylim=c(13.0, 18.0),
    xlab=" ", ylab="100m ( )",
    main=" ")
    ( )
    :
    2023 5 — 2023-12 – p.12/16

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  13. 0 20 40 60 80 100
    13 14 15 16 17 18
    ↓┦㛵ࡢ౛
    ⱥㄒࡢヨ㦂⤖ᯝ
    100m㉮ࡢࢱ࢖࣒ (⛊)
    2023 5 — 2023-12 – p.13/16

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  14. 3
    1 2 3
    3 <- data.frame( = 1$ , = 1$ ,
    = 2$ ,
    = 2$ )
    plot( 3)
    2 12
    :
    plot
    2023 5 — 2023-12 – p.14/16

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  15. ⱥㄒ
    20 40 60 80
    20 40 60 80 100
    13 14 15 16 17
    20 40 60 80
    ᩘᏛ
    㐠ື᫬㛫
    0 5 10 15
    13 14 15 16 17
    20 40 60 80 100
    0 5 10 15
    ▷㊥㞳
    2023 5 — 2023-12 – p.15/16

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  16. 2023 5 — 2023-12 – p.16/16

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