[통계, 회귀분석, 프로빗 회귀분석, 로지스틱 회귀분석] Logistic Regression & Probit Regression

 1  [통계, 회귀분석, 프로빗 회귀분석, 로지스틱 회귀분석] Logistic Regression & Probit Regression-1
 2  [통계, 회귀분석, 프로빗 회귀분석, 로지스틱 회귀분석] Logistic Regression & Probit Regression-2
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[통계, 회귀분석, 프로빗 회귀분석, 로지스틱 회귀분석] Logistic Regression & Probit Regression에 대한 자료입니다.
목차
I. Logistic regression
A. Extension of multiple regression but the dv is categorical
B. Value being predicted represents a probability, and it varies between 0 and 1
C. Possible to use categorical ivs (dummy coded, but won’t here)
D. Key concept: logit
E. SPSS (example with the Helping3.sav data set)
본문내용
Logistic Regression & Probit Regression by SPSS
I. Logistic regression
A. Extension of multiple regression but the dv is categorical
B. Value being predicted represents a probability, and it varies between 0 and 1
C. Possible to use categorical ivs (dummy coded, but won’t here)
D. Key concept: logit
1. natural logarithm (ln) of the odds
2.
3. Therefore, prob success + ? + + + +
E. SPSS (example with the Helping3.sav data set)
1.
참고문헌
Logistic Regression & Probit Regression
하고 싶은 말
Logistic Regression & Probit Regression