Statistics
Methods for collecting, analyzing, interpreting, and presenting data.
Statistics is the discipline of learning from data, including how data are collected, summarized, modeled, and interpreted. Descriptive statistics summarize observed data; inferential statistics use a sample and assumptions to reason about a broader population or process. A numerical summary is meaningful only alongside its definitions and context.
Define the question, population, units, variables, and time period before choosing a statistic. Ask how observations were selected and measured, which groups may be missing, and whether the data quality fits the question. Large datasets can still be biased or incomplete; precision in calculation does not repair a weak design.
Show the scale, denominator, and uncertainty where relevant. An average can hide variation; a rate needs a population and time window; an association does not establish cause. Explain assumptions and practical significance as well as statistical results, and avoid implying more certainty than the data support.
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