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--- logistic_regression [2023/11/30 08:00] – [Logistic Regression] hkimscil
+++ logistic_regression [2023/12/06 14:01] – hkimscil
@@ Line 1: / Line 1: @@
 ====== Logistic Regression ======
-<WRAP half column>
-[[https://elwlsek.tistory.com/466|Log의 성질]]
-{{youtube>nz-FrbAa8dY}}
-Logistic Regression Tutorial
-\begin{align}
-y = b_{0} + b_{1}x \\
-p = \frac{1} {1 + e^{-y}} \\
-ln(\frac{p}{1-p}) = b_{0} + b_{1}x \\
-\end{align}
-</WRAP>
-<WRAP half column>
-{{youtube>vN5cNN2-HWE}} Logistic Regression Details Pt1: Coefficients
-{{youtube>BfKanl1aSG0}} Logistic Regression Details Pt 2: Maximum Likelihood
-{{youtube>xxFYro8QuXA}} Logistic Regression Details Pt 3: R-squared and p-value
-</WRAP>
 ====== e.g. 1 ======
 https://stats.idre.ucla.edu/r/dae/logit-regression/
@@ Line 134: / Line 116: @@
 wald.test(b = coef(mylogit), Sigma = vcov(mylogit), L = l)
 </code>
+====== 관련 동영상 ======
+<WRAP half column>
+[[https://elwlsek.tistory.com/466|Log의 성질]]
+{{youtube>nz-FrbAa8dY}}
+Logistic Regression Tutorial
+\begin{align}
+y = b_{0} + b_{1}x \\
+p = \frac{1} {1 + e^{-y}} \\
+ln(\frac{p}{1-p}) = b_{0} + b_{1}x \\
+\end{align}
+</WRAP>
+<WRAP half column>
+{{youtube>vN5cNN2-HWE}} Logistic Regression Details Pt1: Coefficients
+{{youtube>BfKanl1aSG0}} Logistic Regression Details Pt 2: Maximum Likelihood
+{{youtube>xxFYro8QuXA}} Logistic Regression Details Pt 3: R-squared and p-value
+</WRAP>
 {{tag> statistics r "logistic regression" "logit analysis" "multiple regression"}}