Hello everyone,
I tried to understand the relationship between temperature and the
death of an organism by using logistic regression.
glm(formula = Death ~ Temperature, family = binomial(link = "logit"),
data = mydata)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -87.9161 7.7987 -11.27 <2e-16 ***
Temperature 2.9532 0.2616 11.29 <2e-16 ***
>From the above summary, I could understand that log odds of death =
-87.9161 + 2.9532*Temperature. Odds=exp(log[odds]). Probability =
odds/(1+odds)
Assuming my data is randomly normal distributed with (u=0, standard
deviation=0.35), and I want to run it for n=10,000, how do I get to
probability from log odds?
Regards,
Eddie
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