EDA's final week is about "honestly summarizing data numerically and validating whether that summary is trustworthy." Before MLS-C01 asks about algorithms, it tests statistical intuition. Is the distribution skewed? Should you trust mean or median? Does the sample fairly represent the population?—misunderstanding these leads to wrong conclusions, regardless of model choice.
Today we build EDA's statistical foundation: distribution, central tendency and dispersion, how transformations affect distributions, and sample versus population.
Don't compute means first. Look at distribution shape first