差分

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81 バイト追加 、 2023年2月4日 (土) 18:05
</math>
Here Because <math>\Leftrightarrow \frac {\left ( \dfrac{p\prime}{1-p\prime} \right )}{ \left ( \dfrac{p}{1-p} \right ) }</math> is the odds ratio of the probablity <math>p\prime</math> after when 1 is added to <math>X_1</math> to the probability <math>p</math>, so  <math>\color{red}{e^{b_1}}</math> or <math>\color{red}{\exp (b_1)}</math> is the conversion of coefficient <math>b_1</math> to obtain the '''odds ratio when of outocome probabilities''' before and after variable <math>X_1</math> gains 1.
==Generalized linear model==

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