PSYC 1100 A10 SPRING 2025 02 Research Methods KPU Courses

Introduction to Research Methods in Psychology

• Importance of research methods in psychology for foundational understanding.

The Need for Research

• Competing Hypotheses: The phenomenon where contradictory claims exist in society. Examples include:

  • Birds of a feather flock together vs. Opposites attract: Both claims can't be true simultaneously but might be valid under different conditions.

  • Examples of competing hypotheses such as:

    • You can't teach an old dog new tricks vs. You're too old to learn.

    • Nothing ventured, nothing gained vs. Better safe than sorry.

• Hindsight Bias: The tendency to believe one could have predicted an event after it has occurred.

  • Examples:

    • Claims of knowing outcomes post-factum (i.e., Nick Cannon on The Masked Singer).

    • Trump's quotes regarding COVID-19 show hindsight bias (contradictory statements).

• Overconfidence: A cognitive bias where individuals believe they know more than they actually do.

  • Activity involving estimating time to solve anagrams illustrates this concept.

  • Research shows majority of participants underestimate time and overestimate their abilities.

• Follow-up Study: Predictions about future events show participants' overconfidence; they were more confident than correct.

Goals of Behavioral Science

• Four Goals:

  1. Describing behavior

  2. Predicting behavior

  3. Determining the causes of behavior

  4. Understanding or explaining behavior

1. Describing Behavior

• First step of theory formation. Example: Observing a class and noting note-taking methods.

• Descriptive Statistics: Used to summarize data; does not explain differences.

• Example research questions:

  • Most popular movie genres among adults 60+?

  • Fast food chain preference in the US? (Answer: Chick Fil A)

  • Online activity among 8-18 year olds (with visual statistics).

2. Predicting Behavior

• Can we predict behaviors based on certain variables? (e.g., note-taking styles by year in university).

• Predictive Modeling: Understanding relationships between variables:

  • Independent variable: What is manipulated.

  • Dependent variable: What is measured.

• Examples:

  • Does extroversion predict number of sexual partners?

  • Can intelligence be predicted by education years?

  • Does aggression correlate with height?

3. Determining Causes of Behavior

• Correlation does not imply causation. Establishing direct relationships is crucial.

  • Empirical evidence needed to claim causality (e.g., does watching violent TV cause aggression?).

• Example finding from the APA on violence's relationship with aggression, emphasizing predictive rather than causative language.

4. Explaining Behavior

• Establishing causation leads to needing explanations.

• Possible mechanisms involve modeling and psychological desensitization. Further studies are essential to refine theories.

Scientific Method Overview

• Cyclical Process:

  1. Start with a theory.

  2. Generate hypotheses.

  3. Collect data.

  4. Analyze data and refine theory.

Step 1: Theory

• A scientific theory organizes ideas about phenomena.

• Must be testable and lead to hypothesis generation.

Step 2: Hypotheses

• An educated guess that forecasts behavior. Examples using ink color impacting learning motivation.

• Hypotheses must be falsifiable.

Step 3: Data Collection Methods

1. Descriptive Studies: Help describe behavior.

   • Case Studies: In-depth analysis of an individual/group, but cannot generalize results.

   • Naturalistic Observation: Observing individuals in their natural environments without interference.

   • Surveys: Collect self-reported data; easy to collect but bias and representativity issues.

2. Correlational Studies: Measure how variables relate without manipulation.

   • Benefits: No need to manipulate variables, can explore multiple variables simultaneously.

   • Limitations: Correlation does not imply causation; potential third variable issues.

3. Experimental Studies: Manipulate one variable to observe effects.

   • Features control and experimental groups. Essential for establishing cause and effect claims.

   • Confounding variables must be managed to ensure validity of results.

Summary Table of Research Types

• Descriptive, Correlational, and Experimental designs to provide various insights into human behavior.

Analyzing Data

• Descriptive Statistics: Summaries of data, highlighting trends without explaining differences.

• Inferential Statistics: Used to make generalizations about populations based on sample data.

Research Exercise and Discussion

• Optional activity: Design a correlational and experimental study based on proposed research questions.

• Read an article on Extra Sensory Perception (ESP) and analyze it through the lens of the scientific method.

Conclusion

• Importance of research methods in building a foundation for understanding psychology. Continuous learning encouraged.