Lecture on Types of Variables

Introduction

• Context: Identifying factors that influence student performance.
• Examples of factors:
  • Difficulty understanding instructions
  • Sleeping instead of studying
  • Time management issues
  • Lack of focus

Definition of a Variable

• Variable: An entity that can take on different values and impact study results.
• Examples: Age, gender, IQ level, lifestyle, temperature, medical treatment.
• Purpose: To understand differences in research studies.

Classifications of Variables

Numeric Variables

• Definition: Describe measurable numerical quantities (quantitative data).
• Types:
  • Continuous/Interval Variables: Can assume any value between real numbers.
    • Examples:
      • Time (hours, minutes, seconds)
      • Age (years, months, days)
      • Weight (grams, kilograms)
      • Height (feet, inches)
  • Discrete Variables: Assume whole number values.
    • Examples:
      • Class attendance
      • Number of establishments
      • Number of children

Categorical Variables

• Definition: Describe quality or characteristics (qualitative data).
• Types:
  • Ordinal Variables: Values can be ordered or ranked.
    • Examples:
      • Clothing size
      • Academic ranking
      • Levels of satisfaction
      • Salary scale
  • Nominal Variables: Values cannot be logically ordered.
    • Examples:
      • Learning styles
      • Language spoken
      • Blood type
      • Plate numbers
  • Dichotomous Variables: Only two categories (e.g., yes/no).
  • Polychotomous Variables: Multiple categories (e.g., performance level).

Experimental Variables

• Definition: Determine causal relationships.
• Types:
  • Independent Variables: Cause changes in other variables (causal variables).
  • Dependent Variables: Change as a result of independent variables (effect variables).
  • Control Variables: Held constant to observe differences in outcomes.
  • Moderator Variables: Change relationship under different conditions.
  • Extraneous Variables: Existing variables that might influence study results.

Non-Experimental Variables

• Definition: Cannot be manipulated by researcher.
• Types:
  • Predictor Variables: Affect other variables in non-experimental studies.
  • Criterion Variables: Influenced by predictor variables.

Conclusion

• Understanding and classifying variables helps in detailing how they interact and affect each other in studies, contributing to meaningful discussions on study outcomes.