Exercise 1 – Estimating \( \mu \) in Gaussian GLM
You're solving a regression problem. That means, for every input \( x \), the target variable \( y \) is drawn from a Gaussian distribution:
\[ y \sim \mathcal{N}(\mu, \sigma^2) \]Question:
Which picture correctly describes the situation: