Data Analysis / Basic: Questions and Trustworthy Tables

Data Analysis β€” Basic: Questions and Trustworthy Tables

Define observations and build auditable summaries from typed, validated records.

6 lessons Β· No account required

What you will learn

  • State grain, units, and analytical scope.
  • Read and clean bounded synthetic tables.
  • Compute descriptive summaries with explicit denominators.

  1. Questions, Grain, and Provenance

    Translate a vague request into a measurable question and identify exactly what one row and one reported number represent.

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  2. Data Types, Measurement, and CSV

    Read tabular text under an explicit schema and keep identifiers, quantities, units, and encodings distinct.

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  3. Cleaning and Validation Rules

    Transform records deliberately, preserve raw evidence, and distinguish repairing representation from changing the underlying claim.

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  4. Missing Values and Duplicate Records

    Treat absence and repetition as properties to investigate, preserving their effect on the population and denominator.

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  5. Descriptive Statistics and Distributions

    Describe location and variation together and choose summary definitions that match the data and the question.

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  6. Grouping, Rates, and Denominators

    Build group summaries whose weights, missing values, and eligibility rules answer the same question at every level.

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