Unit 1, Lesson 7: Experiments and Correlations

Introduction

• Focus of this lesson: Experiments and correlations
• Comparison and contrast of research methods including experiments

Experiments

• Definition: Research methods where variables are manipulated
• Variables:
  • Independent Variable: Controlled by the researcher
  • Dependent Variable: Changes in response to the independent variable; often a behavior or mental process

Examples

• Breastfeeding and Intelligence:
  • Independent Variable: Breastfeeding
  • Dependent Variable: Baby's IQ
• Scenarios for Practice:
  1. Reading skill after different classes
  2. Memory after varying sleep conditions
  3. Walking program and lung capacity
  4. Driving simulation and cell phone use

Challenges in Experiments

• Participant Expectations: Can lead to the placebo effect
• Random Assignment: Necessary to avoid bias
• Experimenter Bias: Can be mitigated by single/double blind procedures
  • Single Blind: Participants unaware of group allocation
  • Double Blind: Both participants and researchers unaware of group allocation

Correlations

• Definition: Statistical measure of relationship between two variables
• Types:
  • Positive Correlation: Both variables increase together
  • Negative Correlation: One variable increases as the other decreases

Examples

• Positive Correlation: Sports participation and higher grades
• Negative Correlation: More TV leads to less reading
• Correlation Coefficient: Numeric representation of correlation strength; ranges from -1 to 1

Important Concepts

• Correlation vs. Causation:
  • Correlation does not imply causation
  • Cause and effect only determined through experiments
  • Example: Toaster ownership and birth rates in Taiwan

Further Discussion

• Scatter Plots: Used to visually represent correlations
• Complex Relationships: Example of low self-esteem and depression; multiple factors could be involved

Conclusion

• Understanding the distinction between correlation and causation is crucial
• Experiments are needed to establish cause-and-effect relationships
• Continued exploration of these topics in class with visual and practical examples