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From Raw Data to a Data Set
Turn raw records into a structured data set by identifying observations, variables, rows, columns, and data dimensionality.
24 min3 هدف
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ماژول 2
Plan credible data collection by defining variables, measurement levels, populations, samples, survey designs, data sources, and bias risks.
شروع ماژولنشان
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12 درس، حدود 354 دقیقه.
Turn raw records into a structured data set by identifying observations, variables, rows, columns, and data dimensionality.
Classify variables by the kind of information they contain and avoid treating numeric labels as measured quantities.
Recognize when data describes change through time, a snapshot across units, or a panel-style combination.
Use nominal, ordinal, interval, and ratio levels to decide which comparisons and calculations are meaningful.
Design and summarize rating scales while respecting midpoint choices, endpoint labels, and ordinal interpretation.
Connect target populations, frames, samples, censuses, parameters, and statistics in a practical study plan.
Compare simple random, systematic, stratified, and cluster sampling designs for finite populations.
Evaluate judgment, convenience, focus group, POS, loyalty, and web analytics data with a bias-aware lens.
Separate sample-size precision from nonresponse, selection, coverage, response, measurement, interviewer, and sampling errors.
Judge public, business, official, private, vendor, and web data sources by documentation, reliability, access, and citation needs.
Design survey questions that match goals, constraints, target population, response scales, and data-quality checks.
Design a complete data collection plan for an online education business and summarize synthetic pilot survey evidence.