Lecture Two: Research Methods Notes

Introduction to Research Methods

• Lecturer: Dr. Donna Anderson, School of Psychology, Port Macquarie campus
• Focus of Research: Children, young people, mental health, and well-being
• Learning Objectives: Important to review the entire chapter for examination purposes; not all objectives are covered in the lecture.

Importance of Learning Research Design and Statistics

• Human Error: People are prone to error due to cognitive shortcuts when processing stimuli. This leads to mistakes in perception and decisions.
• Scientific Method: Psychologists utilize the scientific method to gather data, test hypotheses, and minimize errors in understanding human behavior.
• Evidence-based Practice: Psychologists base assessments and treatments on peer-reviewed academic research.
• Critical Evaluation: Understanding and evaluating psychological research is essential for future practice.

Modes of Thinking

• Intuitive Thinking (System One): Fast, automatic; relies on heuristics (mental shortcuts); prone to error (e.g., misconceptions about direction).
• Analytic Thinking (System Two): Slower, requires effort; seeks to analyze and understand deeply.

Key Research Methods in Psychology

1. Naturalistic Observation

• Description: Researchers observe behavior in a natural setting without manipulation.
• Advantage: High external validity; findings generalize well to real-world scenarios.
• Disadvantage: Low internal validity; cannot establish cause-and-effect relationships.

2. Case Studies

• Description: In-depth study of one or a few individuals over an extended time.
• Advantage: Useful for understanding rare or complex psychological phenomena and generating hypotheses.
• Disadvantage: Limited generalizability; often relies on anecdotal evidence without causal conclusions.

3. Surveys

• Description: Self-report method to gather data on attitudes, opinions, or experiences from a sample.
• Representative Sample: Crucial for generalizability; random sampling preferred over convenience sampling.
• Key Terms: Reliability (consistency of measurements) and Validity (accuracy of what is being measured).

4. Experimental Designs

• Description: Researcher manipulates an independent variable to observe effects on a dependent variable; participants are randomly assigned to conditions.
• Causation: Allows for causal inferences when well-designed.
• Challenges: Potential confounding variables, placebo effect, and biases.

Advantages and Disadvantages of Research Methods

Correlation vs. Causation

• Correlation: Indicates an association but does not imply causation.
• Example Misinterpretation: Strong correlation between the number of churches and crime rates does not mean one affects the other.
• Illusory Correlations: Overemphasizing single instances without considering broader data leads to misconceptions.

Importance of Statistics

Descriptive Statistics

• Central Tendency: Mean (average), median (middle score), mode (most common score).
• Variability: Range (difference between max and min), standard deviation (how spread out scores are).

Inferential Statistics

• Purpose: To make generalizations from sample data to a larger population.
• Statistical Significance: Determined by p-values; a p-value < 0.05 indicates significant results unlikely to be due to chance.
• Practical Significance: Evaluates the real-world implications of results, beyond statistical significance.

Conclusion

• Application of Knowledge: Critical thinking in evaluating research, distinguishing between correlation and causation.
• Practical Exercise: Observe media claims about scientific findings; identify misrepresentations and discuss implications in class.