Group 5 Variables

Group S Variables

  • Members: Mauricio Cortez

What is a Variable?

  • Definition: Variables refer to people, places, objects, or phenomena that researchers aim to measure.

  • Characteristics:

    • Can take on more than one value.

    • Values can be represented as words or numbers.

Attribute

  • Definition: A specific value on a variable.

Example of Variables

  • Gender: Male, Female

  • Agreement Levels: Strongly disagree, Disagree, Neutral, Agree, Strongly agree

Ice Breaker

Research Topics

  • The Effect of Co-Curricular Activities on the Academic Achievements of Students

  • The Impact of Social Media on the Mental Health of Adolescents and Young Adults

  • The Effect of Sports Drinks on the Athletic Performance of Athletes

  • Feasibility of Dried Leaves in the Production of Paper

The Nature of Variables

Types of Variables

  • 1. Nominal Variables:

    • Definition: Represent categories that cannot be ordered.

    • Examples:

      • Gender: Male, Female, Other.

      • Marital Status: Single, Married, Divorced, Widowed.

      • Nationality: Filipino, American, Spanish, Chinese, etc.

  • 2. Ordinal Variables:

    • Definition: Represent categories that can be ordered.

    • Examples:

      • Socioeconomic Status: Low Income, Middle Income, High Income.

      • Education Level: High School, BS, MS, PhD.

      • Income Level: Less than 30K, 30K-50K, Over 50K.

  • 3. Interval Variables:

    • Definition: Values with an evenly dispersed range of numbers.

    • Examples:

      • Temperature in Fahrenheit or Celsius.

      • Time.

  • 4. Ratio Variables:

    • Definition: Values with an absolute zero.

    • Examples:

      • Weight.

      • Length.

Kinds of Variables

  • Independent Variable:

    • Definition: Stands alone and is not changed by other variables.

    • Role: It is the cause or influence and affects outcomes.

  • Dependent Variable:

    • Definition: What researchers measure; it depends on the independent variable.

    • Role: It reflects the outcomes influenced by the independent variable.

Concept of Influence

  • Hack: "The independent variable causes a change in the dependent variable, not the other way around."

Common Research Examples

  • The Effects of Social and Emotional Learning on Student Well-Being

  • The Influence of Early Childhood Education on Academic Achievement

  • The Impact of Blended and Online Learning on Educational Outcomes

Intervening or Mediating Variables

  • Definition: Illustrates the effects of the independent variable on the dependent variable, explaining connections among variables.

  • Example: Wealth (independent) → Access to quality health care (intervening) → Long life span (dependent).

Moderating Variables

  • Definition: Factors that may influence the relationship between independent and dependent variables.

  • Role: Can strengthen or weaken the effect of intervening variables.

  • Example: Economic status (independent) → Frequency of doctor visits (dependent); age as a moderating variable affecting the relationship.

Control Variables

  • Definition: Constants that do not change during a study; have no impact on other variables.

  • Example: In plant experiments, control variables include consistent amounts of fertilizer and water.

Confounding Variables

  • Definition: Unmeasured variables that can influence the relationship between other variables, leading to false correlations.

  • Example: In a study linking movie genre to candy consumption, time of day can act as a confounding variable affecting hunger levels.

Variables Relationship

  • Definition: Assesses accuracy of conclusions based on variables.

Types of Relationships

  • Linear Relationships: Represented as straight lines on scatter plots.

    • Positive Relationship: Both variables move in the same direction.

      • Example: Increased exercise leads to better results.

    • Negative Relationship: Variables move in opposite directions.

      • Example: Higher outside temperature may reduce outdoor activity willingness.

  • Non-Linear Relationships: Represented by curved lines; do not follow linear patterns.

    • Example: Battery charging duration does not equate to corresponding charge increase.

  • Unrelated Relationships: No correlation between two variables.

    • Example: Price of books vs. price of pillows.

Other Types of Variables

  • Discrete Variables: Countable and can only take specific values.

    • Example: Number of pages in a book, number of students in a classroom.

  • Categorical Variables: Represent data divided into groups.

    • Example: Hair color, race.

Conclusion

  • Thank you for your attention!

References

  • Apolonio, J. and Basilan, Ma. (2017). Practical Research 2. Unlimited Books.

  • Prieto, N. et al. (2017). Practical Research 2 (Quantitative). Lorimar Publishing, Inc.

  • Drew, C. (2023, August 14). Variable Examples. Retrieved from Helpful Professor. https://helpfulprofessor.com/nominal-variable-examples/

  • And other sources.