May 2022
Beginner to intermediate
448 pages
13h 7m
Korean
book
밑바닥부터 시작하는 데이터 과학 데이터 분석을 위한 파이썬 프로그래밍과 수학·통계 기초
by Joel Grus, Hangyeol Kim, Seongju Ha, Eunjung Park
Content preview from 밑바닥부터 시작하는 데이터 과학 데이터 분석을 위한 파이썬 프로그래밍과 수학·통계 기초
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Data Science
104
normal
_
two
_
sided
_
bounds(0.95, mu, sigma) # [0.4940, 0.5560]
지금 얘기하고 있는 것은 p가 아닌 구간에 대한 얘기다. 실험을 수없이 반복하면 전체 실험
의 95%에서는 ‘진짜’ 파라미터 p가(진짜 파라미터 p는 매번 동일할 것이다) 관측된 신뢰
구간 사이에(신뢰구간은 매번 다를 수도 있다) 존재할 것이다.
이 경우
0
.
5
는 신뢰구간 안에 있기 때문에 동전은 공평하지 않다고 결론을 내릴
수가 없다.
반대로, 앞면이
540
번 나왔다면
p
_
hat = 540 / 1000
mu = p
_
hat
sigma = math.sqrt(p
_
hat * (1 - p
_
hat) / 1000) # 0.0158
normal
_
two
_
sided
_
bounds(0.95, mu, sigma) # [0.5091, 0.5709]
‘공평한 동전’에 대한 확률은 계산된 신뢰구간 밖에 존재하게 된다. 공평한 동전
이라는 가설은, 가설이 참이라면 모든 경우의
95
%에 대해 가설검정을 통과하지
못하게 된다.
7.5
p 해킹
귀무가설을 잘못 기각하는 경우가
5
%인 가설검정은 정의에서 알 수 있듯이 모
든 경우의
5
%에서 귀무가설을 잘못 기각한다.
from typing import List
def run
_
experiment() -> ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.