Statistics

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  • Statistics: science of collecting, organizing, presenting, analyzing, interpreting numerical data for efficient decision-making.

  • Key applications: marketing, accounting, quality control, sports, education, politics, medicine.

  • Branches:

    • Descriptive Statistics – summarizes data via numbers, charts, graphs, tables.

    • Inferential Statistics – draws conclusions about a population from a sample and measures reliability.

  • Population vs. Sample: population = complete set; sample = subset used when full census impractical.

  • Variables:

    • Qualitative – categorical (e.g., name, gender, address).

    • Quantitative – numeric; classified as
      • Discrete: countable values (e.g., number of children).
      • Continuous: any value in an interval (e.g., height).

  • Levels of Measurement (intro): Nominal described here — labels only; only counting applicable.

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  • Levels of Measurement (cont.):

    • Ordinal – ranking; indicates order, not magnitude.

    • Interval – equal intervals; arbitrary zero (e.g., temperature ^\circ C).

    • Ratio – all interval properties plus absolute zero (e.g., weight); all stats applicable.

  • Data Collection: systematic gathering to answer questions/test hypotheses.

    • Sources: Primary vs. Secondary data.

    • Primary data methods:
      1. Direct Personal Interview – face-to-face; rich data, but time-consuming/expensive/bias risk.
      2. Questionnaire (Indirect) – suited for large samples.
      • Design principles: keep short, choose type, clear wording/order, intro letter, instructions, translation, pretest.

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  • Questionnaire Types:

    • Open-ended – free text; detailed but hard to analyze, lower response.

    • Closed-ended – fixed options; easy to analyze, high response but may bias/frustrate.

  • Other Primary Methods:
    3. Focus Group – 6–12 similar participants; faster/cheaper than interviews; response bias possible.
    4. Experiment – researcher controls conditions to study cause–effect; objective but costly, prone to recording error.
    5. Observation – record phenomena as they occur; objective, but limited info and costly.

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  • Secondary Data: previously collected; cheaper & quicker.
    Advantages: economical, time-saving, comparative base, new insights.
    Disadvantages: questionable accuracy, possible irrelevance, limited availability/cost.

  • Key Secondary Sources:
    1. Published reports (newspapers/periodicals).
    2. Financial data in annual reports.
    3. Institutional records.
    4. Government department reports (e.g., census).

  • Consequences of Poor Data Collection:
    • Inaccurate answers • Irreproducible studies • Wasted resources • Misleading future research • Faulty public policy • Potential harm to subjects.