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Introductory Statistics: Unit 1 Key Concepts

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Termini in questo insieme (21)

  • Statistics (the science)

    Statistics (the science) is the science of collecting, organizing, and interpreting data.

  • Population vs. Sample

    Population is the complete set of people or things studied; Sample is a subset of the population from which data are obtained.

  • Population parameter vs. Sample statistic

    A population parameter describes a characteristic of the population (usually unknown). A sample statistic describes a characteristic of the sample and is calculated from raw data.

  • Margin of error and confidence interval

    Confidence interval = sample statistic ± margin of error; it estimates the range likely to contain the population parameter.

  • Simple random sample (SRS)

    Every possible sample of a given size has an equal chance of selection, like drawing names from a hat.

  • Cluster sampling

    Divide population into groups, randomly select some groups, then study every member of those groups.

  • Stratified sampling

    Divide population into groups (strata), then randomly select some members from every group.

  • Bias in sampling

    A study is biased if its design favors certain results, often due to non-representative samples or voluntary participation.

  • Observational study vs. Experiment

    Observational study: observe without influencing; Experiment: apply treatment and observe effects; only experiments can prove cause.

  • Confounding variable

    A variable that mixes effects with the variable of interest, making it impossible to isolate the specific effect.

  • Single-blind vs. Double-blind

    Single-blind: participants unaware of group assignment; Double-blind: neither participants nor experimenters know group assignments.

  • Qualitative vs. Quantitative data

    Qualitative: non-numerical categories or labels; Quantitative: numerical counts or measurements.

  • Discrete vs. Continuous data

    Discrete: countable distinct values; Continuous: any value in an interval, measured.

  • Random error vs. Systematic error

    Random error: unpredictable, no pattern; Systematic error: consistent bias affecting all measurements similarly.

  • Absolute error and Relative error

    Absolute error = measured value − true value; Relative error = (absolute error ÷ true value) × 100%.

  • Accuracy vs. Precision

    Accuracy: closeness to true value; Precision: level of detail or exactness in measurement.

  • Absolute change vs. Relative change

    Absolute change = new value − reference value; Relative change = (absolute change ÷ reference value) × 100%.

  • Percentage points vs. Percent change

    Percentage points: absolute difference (add/subtract); Percent change: relative difference (multiply percent by original value).

  • Frequency table components

    Includes categories, frequency (count), relative frequency (proportion), and cumulative frequency (running total).

  • Bar graph vs. Histogram

    Bar graph: qualitative data, bars separated; Histogram: quantitative data, bars touch, ordered bins.

  • Common graph distortions

    Watch for misuse of area/volume in pictures, non-zero axis starts, nonlinear scales, misleading percentage change graphs, and decorative pictograms.