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
P 値と有意差/分散分析 / P-value, Significant Difference ...
Search
Kenji Saito
PRO
January 03, 2025
Technology
0
64
P 値と有意差/分散分析 / P-value, Significant Difference and Analysis of Variance
早稲田大学大学院経営管理研究科「企業データ分析」2024 冬の第9-10回で使用したスライドです。
Kenji Saito
PRO
January 03, 2025
Tweet
Share
More Decks by Kenji Saito
See All by Kenji Saito
続・インクルーシブな社会へ / Continuing Towards an Inclusive Society
ks91
PRO
0
10
AGI (人工一般知能) と創る新しく奇妙な社会 / New and Stranger Society built with AGI
ks91
PRO
0
53
回帰分析/大規模言語モデルと統計 / Regression Analysis, Large Language Models and Statistics
ks91
PRO
0
60
多重比較/相関分析 / Multiple Comparison and Correlation Analysis
ks91
PRO
0
59
アカデミーキャンプ 2025冬「考えるのは奴らだ」 / Academy Camp 2025 Winter - Live and Let Think DAY 3
ks91
PRO
0
55
アカデミーキャンプ 2025冬「考えるのは奴らだ」 / Academy Camp 2025 Winter - Live and Let Think DAY 2
ks91
PRO
0
42
アカデミーキャンプ 2025冬「考えるのは奴らだ」 / Academy Camp 2025 Winter - Live and Let Think DAY 1
ks91
PRO
1
68
インクルーシブな社会へ / Toward an Inclusive Society
ks91
PRO
0
14
関連2群のt検定/独立2群のt検定 / Related 2-group t-test and independent 2-group t-test
ks91
PRO
0
71
Other Decks in Technology
See All in Technology
Ask! NIKKEIの運用基盤と改善に向けた取り組み / NIKKEI TECH TALK #30
kaitomajima
1
420
現場で役立つAPIデザイン
nagix
19
6.4k
5分で紹介する生成AIエージェントとAmazon Bedrock Agents / 5-minutes introduction to generative AI agents and Amazon Bedrock Agents
hideakiaoyagi
0
190
Next Step: Play Time!
trishagee
2
160
ビジネスと現場活動をつなぐソフトウェアエンジニアリング~とあるスタートアッププロダクトの成長記録より~
mizunori
0
130
What's New in OpenShift 4.18
redhatlivestreaming
0
1.2k
技術的負債解消の取り組みと専門チームのお話 #技術的負債_Findy
bengo4com
1
1.1k
君も受託系GISエンジニアにならないか
sudataka
0
230
Amazon GuardDuty Malware Protection for Amazon S3のここがすごい!
ryder472
1
120
開発者が自律的に AWS Security Hub findings に 対応する仕組みと AWS re:Invent 2024 登壇体験談 / Developers autonomously report AWS Security Hub findings Corresponding mechanism and AWS re:Invent 2024 presentation experience
kaminashi
0
170
Datadogとともにオブザーバビリティを布教しよう
mego2221
0
120
Ask! NIKKEI RAG検索技術の深層
hotchpotch
13
2.7k
Featured
See All Featured
Raft: Consensus for Rubyists
vanstee
137
6.8k
Scaling GitHub
holman
459
140k
Why You Should Never Use an ORM
jnunemaker
PRO
55
9.2k
Fashionably flexible responsive web design (full day workshop)
malarkey
406
66k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
27
1.9k
Optimising Largest Contentful Paint
csswizardry
34
3.1k
Into the Great Unknown - MozCon
thekraken
34
1.6k
Bootstrapping a Software Product
garrettdimon
PRO
305
110k
Git: the NoSQL Database
bkeepers
PRO
427
64k
jQuery: Nuts, Bolts and Bling
dougneiner
63
7.6k
YesSQL, Process and Tooling at Scale
rocio
171
14k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
6
530
Transcript
Corporate data analysis — generated by Stable Diffusion XL v1.0
2024 9-10 P (WBS) 2024 9-10 P — 2025-01-06 – p.1/33
https://speakerdeck.com/ks91/collections/corporate-data-analysis-2024-winter 2024 9-10 P — 2025-01-06 – p.2/33
( ) 1 12 2 • 2 12 2 (B
A ) • 3 12 9 • 4 12 9 • 5 12 16 • 6 12 16 t • 7 12 23 2 ( ) t • 8 12 23 2 ( ) t • 9 1 6 P • 10 1 6 • 11 1 20 12 1 20 13 1 27 14 1 27 W-IOI 2024 9-10 P — 2025-01-06 – p.3/33
( 20 25 ) 1 (20 ) • 2 R
( 55 ) • 3 (32 ) • 4 (14 ) • 5 ( Git) (22 ) • 6 ( ) (24 ) • 7 (1) (25 ) • 8 (2) (25 ) • 9 R ( ) (1) — Welch (17 ) • 10 R ( ) (2) — (21 ) • 11 R ( ) (1) — (15 ) • 12 R ( ) (2) — (19 ) • 13 GPT-4 (19 ) • 14 GPT-4 (29 ) • 15 ( ) LaTeX Overleaf (40 ) • 8 (12/16 ) / (2 ) OK / 2024 9-10 P — 2025-01-06 – p.4/33
( Student µ 95% ) 7 2 t ( t
) 2 ( ) 2 d ( ) ← [ 3] σd 2 t 8 2 t ( t ) 2 ( ) ( ) ← [ 4] σ 2 t 2024 9-10 P — 2025-01-06 – p.5/33
2 2 t 1 9 P P 10 H0 HA
k, N, ¯ ¯ x σ2 ( )MSwithin ( )MSbetween MStotal F F 2024 9-10 P — 2025-01-06 – p.6/33
2024 9-10 P — 2025-01-06 – p.7/33
4. t (1) 2 t (2) 2 t (3) 2025
1 2 ( ) 23:59 JST ( ) Waseda Moodle (Q & A ) (1)(2) Discord 2024 9-10 P — 2025-01-06 – p.8/33
. . . . . . 17 14 (1/3( )
) ( ) → 14 ( ) ( ) → 6 → 3 ( ) → 5 ( ) ( OK) 2 t . . . . . . / . . . ( ) 2024 9-10 P — 2025-01-06 – p.9/33
t t ⇒ ( ) A A xA 2 B
B xB 2 df . . . ⇒ t σ z0.05 . . . ⇒ ( ) t 2024 9-10 P — 2025-01-06 – p.10/33
N (1/2) 2 t 2 2 “ ” 1. 1
2 2. 3. - 2 (n − 1) 4. ÷ ÷ t 5. t (n − 1) t t ⇒ . . . 0 ( ) 2024 9-10 P — 2025-01-06 – p.11/33
N (2/2) 2 t 2 2 1 2 1 2
2 “ ” 1. 2 1 2 2. 3. ( -2) 4. t 1÷ 2 t 5. t (n1 + n2 − 2) t t ⇒ 2024 9-10 P — 2025-01-06 – p.12/33
M ( ) [ 2 t ] 1Day 1Day 1Day
⇒ 2024 9-10 P — 2025-01-06 – p.13/33
K ⇒ . . . 2024 9-10 P — 2025-01-06
– p.14/33
2 t d : µd 0 ( 2 ) :
(1) d d, sd , n, df (2) |d| sd n |t| (3) t0.05 (df) < |t| ( ) R > t.test(sample2, sample1, paired=T) 2024 9-10 P — 2025-01-06 – p.15/33
2 t ( ) 10 ( ) ( ) (
) ( ) ( ) d ( ) d, ( ) sd , ( ) n, ( ) df ( ) t ( ) t ( ) d ( ) sd ( ) n ( ) t df 5% ( ) ( ) ( ) ( ) ( ) 2024 9-10 P — 2025-01-06 – p.16/33
2 t xA xB : µA − µB 0 (
2 ) : (1) xA − xB , sp , nA nB , df (2) |xA − xB | sp nA nB |t| (3) t0.05 (df) < |t| ( ) R > t.test(sample2, sample1, var.equal=T) 2024 9-10 P — 2025-01-06 – p.17/33
2 t ( ) ( ) ( ) ( )
( ) ( ) ( ( ) A B ( ) ) ( ) xA − xB , A B ( ) ( ) sp , ( ) nA nB , ( ) df = nA + nB − 2 ( ) t ( ) t ( ) xA − xB ( ) sp ( ) nA ,nB ( ) t df 5% ( ) ( ) ( ) ( ) ( ) ( ) 2024 9-10 P — 2025-01-06 – p.18/33
K 2 t ( ) ⇒ 2 2024 9-10 P
— 2025-01-06 – p.19/33
N ⇒ (σ) ( σ √n ) ( ) p.121
(standard error) (p.121) (sampling distribution) (p.120) (p.120) ( : ) 2024 9-10 P — 2025-01-06 – p.20/33
K ⇒ . . . AI ( ) . .
. ^^; ( ) 2024 9-10 P — 2025-01-06 – p.21/33
H t 2 Student t t 1 sin(α + β)
= sinαcosβ + cosαsinβ . . . ⇒ 2024 9-10 P — 2025-01-06 – p.22/33
U R ChatGPT ⇒ AI ( ) 2024 9-10 P
— 2025-01-06 – p.23/33
9 P P 2024 9-10 P — 2025-01-06 – p.24/33
α β P P H0 ( ) P 0.05 (P
= 0.015) (P = 0.361) 2024 9-10 P — 2025-01-06 – p.25/33
10 H0 HA k, N, ¯ ¯ x σ2 (
) MSwithin ( )MSbetween MStotal ( SStotal dftotal ) F F 2024 9-10 P — 2025-01-06 – p.26/33
(1/3) k (1) : (2) : σ2 ( ) N(µ,
σ2) µ1 = µ2 = · · · = µk N ( ) ¯ ¯ x ¯ ¯ x = k j=1 nj i=1 xji N (j i N ) 2024 9-10 P — 2025-01-06 – p.27/33
(2/3) ( )MSwithin σ2 MSwithin = SSwithin dfwithin = k
j=1 nj i=1 (xji − ¯ xj )2 N − k ( N− ) ( )MSbetween σ2 MSbetween = SSbetween dfbetween = k j=1 nj (¯ xj − ¯ ¯ x)2 k − 1 ( −1 ) ( H0 σ2 ) 2024 9-10 P — 2025-01-06 – p.28/33
(3/3) MStotal MStotal = SStotal dftotal = k j=1 nj
i=1 (xji − ¯ ¯ x)2 N − 1 ( N − 1 ) : SStotal = SSbetween + SSwithin, dftotal = dfbetween + dfwithin F F = MSbetween MSwithin F0.05 (dfbetween, dfwithin ) < F ( H0 ) 2024 9-10 P — 2025-01-06 – p.29/33
U ( p.227) 20 4 “ U.R” ( anova() )
pp.226–227 2024 9-10 P — 2025-01-06 – p.30/33
2024 9-10 P — 2025-01-06 – p.31/33
5. (1) ( ) (2) 2025 1 16 ( )
23:59 JST ( ) Waseda Moodle (Q & A ) (1)(2) Discord 2024 9-10 P — 2025-01-06 – p.32/33
2024 9-10 P — 2025-01-06 – p.33/33