Levels of Measurements

• What are the three levels of measurement?

  Nominal, ordinal, and interval
• What is the purpose of distinguishing between levels of measurement?

  To decide on statistical tests and displays
• How can psychologists use levels of measurement?

  To choose graphs and statistical tests
• What is nominal data?

  • Lowest level of measurement
  • Separate, discrete categories
  • Cannot be ordered
  • Example: types of fruit
• What is ordinal data?

  • Middle level of measurement
  • Can be ordered
  • Intervals between ranks may differ
  • Example: race finishing positions
• What is interval data?

  • Most detailed level of measurement
  • Equal intervals between values
  • Lacks a true zero point
  • Example: temperature in Celsius
• What is an unsafe scale?

  A measure lacking standardization and reliability
• How can mood scores be converted into ordinal data?

  • Rank scores from lowest to highest
  • Create categories based on score ranges
• How can mood scores be converted into nominal data?

  • Classify scores into categories (e.g., positive, negative)
  • Use labels instead of numerical values
• What are the key terms related to levels of measurement?

  • Levels of Measurement
  • Nominal
  • Ordinal
  • Interval
  • Unsafe scale
• Why is it important to understand levels of measurement in research?

  It determines the type of statistical analysis
• What limitation exists with nominal data?

  It provides the least information about data
• What limitation exists with ordinal data?

  Intervals between ranks may not be equal
• What limitation exists with interval data?

  It lacks a true zero point
• What are the steps to categorize data into levels of measurement?

  1. Identify the type of data (qualitative or quantitative)
  2. Determine if data can be ordered
  3. Assess if intervals are equal
  4. Classify as nominal, ordinal, or interval