๐Ÿ† ์ž๊ฒฉ์ฆ, ์–ดํ•™

[๋น…๋ฐ์ดํ„ฐ ๋ถ„์„๊ธฐ์‚ฌ] ์‹ค๊ธฐ - 3์œ ํ˜• ์นด์ด์ œ๊ณฑ๊ฒ€์ •

๋ฐ์ดํ„ฐํŒ์Šค 2024. 8. 21. 18:06

 

์นด์ด์ œ๊ณฑ์€ ์ ํ•ฉ์„ฑ ๊ฒ€์ •๊ณผ ๋…๋ฆฝ์„ฑ ๊ฒ€์ •์„ ๋ฌผ์–ด๋ณด๋Š”๋ฐ ์†”์งํžˆ ์ ํ•ฉ์„ฑ ๊ฒ€์ •์€ ๋‚˜์˜ฌ ํ™•๋ฅ ์ด ์ ์–ด ๋ณด์—ฌ์„œ ๋นผ๊ณ  ์™ธ์šฐ๊ฒ ์Œ..

์‹œํ—˜๊นŒ์ง€ ๋‚จ์€ ์‹œ๊ฐ„ ๋‹จ 9์‹œ๊ฐ„!! ์•ˆ๋˜๋Š”๊ฑด ์žฌ๋ผ์ž

# ์ ํ•ฉ์„ฑ ๊ฒ€์ •
from scipy.stats import chisquare
statistic,pvalue=chisquare(f_obs=f_obs,f_exp=f_exp)
 
# ๋…๋ฆฝ์„ฑ ๊ฒ€์ •
from scipy.stats import chi2_contigency
statistic, pvalue, dof, expected = chi2_contigency(df)

#๋ฐ์ดํ„ฐ ํ˜•ํƒœ๊ฐ€ ๋‹ค๋ฅผ ๊ฒฝ์šฐ
table=pd.crosstab(df['์นผ๋Ÿผ1'],df['์นผ๋Ÿผ2'])