Why Statistics Matters in Data Science

This opening lesson explains why statistics is central to data science work. It frames statistics as the discipline that helps data scientists move from raw observations to reliable conclusions, especially when data is incomplete, noisy, biased, or collected from only part of a population.

Students learn the difference between describing data, making inferences, estimating uncertainty, and supporting decisions. The lesson also introduces common failure modes in data projects, such as mistaking correlation for causation, trusting misleading averages, ignoring sampling bias, and overinterpreting model results.