# The Gauss Markov Theorem

When studying the classical linear regression model, one necessarily comes across the Gauss-Markov Theorem. The Gauss-Markov Theorem is a central theorem for linear regression models. It states different conditions that, when met, ensure that your estimator has the lowest variance among all unbiased estimators. More formally, Continue reading The Gauss Markov Theorem

# Binomial Distribution

The binomial distribution is closely related to the Bernoulli distribution. In order to understand it better assume that $X_{1},X_{2},...,X_{n}$ are i.i.d (independent, identical distributed) variables following a Bernoulli distribution with $P(X_{i}=1)=\pi$ and $P(X_{i}=0)=1-\pi$.