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Variables and Measurement in Data Analysis

Learn about types of variables, levels of measurement, SPSS settings, measurement error sources, reliability, and validity in data analysis. Enhance your data expertise today!

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Variables and Measurement in Data Analysis

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  1. Variables & Measurement Lesson 4

  2. What are data? • Information from measurement • datum = single observation • Variables • Dimensions that can take on different values • IQ, height, shoe size, hair color • Is not the same for all individuals being measured ~

  3. Measuring Variables • Operational definitions • Variables often abstract • Intelligence, anxiety, fitness, etc. • Need to objectively measure • Hypothesis: Salsa dancing increases fitness • Independent: Salsa dancing • Operational definition? • Dependent: fitness • Operational definition? ~

  4. Levels of Measurement • Limits type of statistical analysis possible • Categorical variable • Discrete: only whole numbers • Frequency data • Number of instances that occur for a category • Continuous (quantitative) variable • represents magnitude • infinite number of values b/n adjacent scale values • Can be discrete: e.g., exam scores ~

  5. Levels of Measurement: Categorical • Nominal scale • categorical • order NOT meaningful • can assign arbitrary values • Ordinal scale • Categorical + meaningful order • No info about magnitude of differences • If assign numerical value, must reflect order ~

  6. Levels of Measurement: Quantitative • Interval scale (numbers) • Continuous or discrete • Equal intervals  equal differences • Ratio scale • same characteristics as interval • Ratios of values must be meaningful for magnitude • scale must have true zero point • Most statistics: interval/ratio treated the same ~

  7. Levels of Measurement: SPSS • Variable view tab • Formatting of variable • Measure • Nominal scale • Ordinal scale • Scale • Interval & ratio • Reminder: IV must be nominal for most statistical tests ~

  8. Measurement Error • Discrepancy • between actual value of observation and the reported value • Sources of measurement error • Sensitivity of measuring instrument • Conscientiousness of observer • Surveys: inaccurate or untruthful • Low reliability of instrument •  unsystematic variation ~

  9. Reliability & Validity • Accurate measurement requires both • Reliability • Consistency of measurement • Criterion validity • Extent instrument actually measures what it claims to measure • Score on IQ test measures intelligence? •  pulse rate a measure of fear? • Important for internal & external validity ~

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