Hi all! It seems that the conference room (203) is empty at the moment in McGiffert House, so I am in that room instead of the lobby today.

@css-model/winter19 In the last question regarding Bayes decision boundary, x1 and x2 should be random uniform variables drawn from the range [-1,1] and not [0,1] as originally indicated in the instructions.

@css-model/winter19 I added an answer key to the repo for the computation problems. The first part varies so much in responses, there is no specific key for it. Feel free to compare your solutions to the key. Again, you don't have to use the same code and functions (or even R - Python is fine and there were many great submissions using Python), but this is one way to achieve the desired result.

On Question 3, Part c the question states to use a normal distribution to approximate the error, stated as ϵ ∼ N(μ=0, θ^2=0.25). As a normal distribution is determined by a mean and a variance/standard deviation, I assume this is supposed to be σ^2 to signify the variance for the normal distribution?