Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
散布図と相関 / Scatter Plots and Correlations
Search
Kenji Saito
PRO
December 09, 2023
Business
0
74
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
PRO
December 09, 2023
Tweet
Share
More Decks by Kenji Saito
See All by Kenji Saito
デジタルトランスフォーメーションと民主主義 / Digital Transformation and Democracy
ks91
PRO
0
5
We Never Took the Kobayashi Maru Test Until Now. What Do You Think of Our Solutions? — Journeys of the Mind Through a No-Win Game
ks91
PRO
0
17
思いつきが武器になる:研究というゲームを始めよう / Ideas Are Your Equipments : Let the Game of Research Begin!
ks91
PRO
0
75
ロボットを雰囲気(ヴァイブ)でプログラミングするこどもたち / Children Vibe-Programming Robots
ks91
PRO
0
23
アカデミーキャンプ 2025 SuuuuuuMMeR「燃えろ!!ロボコン」 / Academy Camp 2025 SuuuuuuMMeR "Burn the Spirit, Robocon!!" DAY 3
ks91
PRO
0
31
アカデミーキャンプ 2025 SuuuuuuMMeR「燃えろ!!ロボコン」 / Academy Camp 2025 SuuuuuuMMeR "Burn the Spirit, Robocon!!" DAY 2
ks91
PRO
0
34
アカデミーキャンプ 2025 SuuuuuuMMeR「燃えろ!!ロボコン」 / Academy Camp 2025 SuuuuuuMMeR "Burn the Spirit, Robocon!!" DAY 1
ks91
PRO
0
160
未来へのフォワードキャスト / Forward Cast to the Future
ks91
PRO
0
88
発表と総括 / Presentations and Summary
ks91
PRO
0
62
Other Decks in Business
See All in Business
透明性レポート(2025年上半期)
mercari_inc
0
1.1k
Tools & Treasures: Find Auction Items That WOW
auctria
PRO
0
170
IT子会社のグローバルトレンド #scrumsendai / Global Trends in IT Subsidiaries
kyonmm
PRO
3
1.1k
月曜日のトラにおけるデータ分析 × AI の取り組み
nishicat
0
510
【DearOne】Dear Newest Member
hrm
2
11k
コーポレートストーリー(新規投資家様向け会社説明資料)
gatechnologies
1
14k
Rakus Career Introduction
rakus_career
0
390k
Corporate Story (GA technologies Co., Ltd.)
gatechnologies
0
180
Strh株式会社 採用資料
strh
0
210
Cloudbase Recruiting Deck / 採用資料
cloudbaseinc
0
240
快適なエンジニアリングライフ実現するための ワークもとい会社ハック / Work Hacks for a More Comfortable Engineering Life
nttcom
6
2.2k
ARI会社説明
arisaiyou
1
16k
Featured
See All Featured
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
33
2.4k
Building Applications with DynamoDB
mza
96
6.6k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
667
120k
Statistics for Hackers
jakevdp
799
220k
Measuring & Analyzing Core Web Vitals
bluesmoon
9
580
The Pragmatic Product Professional
lauravandoore
36
6.9k
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
194
16k
Save Time (by Creating Custom Rails Generators)
garrettdimon
PRO
32
1.6k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
113
20k
YesSQL, Process and Tooling at Scale
rocio
173
14k
Principles of Awesome APIs and How to Build Them.
keavy
126
17k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
34
6k
Transcript
generated by Stable Diffusion XL v1.0 2023 5 (WBS) 2023
5 — 2023-12 – p.1/16
https://speakerdeck.com/ks91/collections/corporate-data-analysis-2023-winter 2023 5 — 2023-12 – p.2/16
( 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
RStudio Git ( ) 2 2023 5 — 2023-12 –
p.4/16
RStudio Git ( ) RStudio Git Git ( GPL) GitHub
Git ( ) RStudio pull 2023 5 — 2023-12 – p.5/16
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
(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
“ .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
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
“ .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
0 5 10 15 20 13 14 15 16 17
18 ㈇ࡢ┦㛵ࡢ 㐌ᙜࡓࡾࡢㄢእ㐠ື㛫 100m㉮ࡢࢱ࣒ (⛊) 2023 5 — 2023-12 – p.11/16
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
0 20 40 60 80 100 13 14 15 16
17 18 ↓┦㛵ࡢ ⱥㄒࡢヨ㦂⤖ᯝ 100m㉮ࡢࢱ࣒ (⛊) 2023 5 — 2023-12 – p.13/16
3 1 2 3 3 <- data.frame( = 1$ ,
= 1$ , = 2$ , = 2$ ) plot( 3) 2 12 : plot 2023 5 — 2023-12 – p.14/16
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
2023 5 — 2023-12 – p.16/16