GLM Binomial Classification Logistic Funtion R

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Generalized linear models are fit using the glm function in R. We specify that the distribution is binomial. The default link function in glm for a binomial outcome variable is the logit. Logistic regression is useful when you are predicting a binary outcome from a set of continuous predictor variables. Note that I didn't use continuous predictor variables in the example, oops.

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Mark! Excellent explanations and very nice presentation format. I have a hearing disability and I can HEAR your presentations clearly. Many good tutorials exist on youtube, but far too many have audio that is awful. Your presentations are excellent. It is easy to concentrate on content without being distracted by noise which I would think is important to everyone, not just those of us with hearing a disability. I find many youtube videos with great content, but I can't listen because the presentation is just too distracting or, in some cases, the audio is so distorted or reverberant, my hearing cannot autocorrelate the audio. Your channel has great content and presentation. Thank you for this valuable educational resource.

dasrotrad

You knew that the model was predicting probability male because when you made 'Sex' a factor, female was considered 0 and male 1 in R.

urielmenalled

Your length observation outputs you 41. This is the length of variables you have in this dataset, which does not help a lot actually. Could you provide the right code? (: Thanks anyways for your work.

Worldofdave

How do you get the main effects from the model?

dyassine

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