Unit 2: Research Methods

Limits of Common Sense

Hindsight Bias

• The tendency to believe, after learning an outcome, that one would have foreseen it.
  
  

Overconfidence

• Our confidence in our knowledge is greater than our objective accuracy.
  
  

Key Terms

• Hindsight Bias
  
  

• Overconfidence
  
  

• Critical Thinking
  
  

The Scientific Attitude

Characteristics

• Curiosity
  
  

• Skepticism
  
  

• Humility
  
  

Critical Thinking

• Thinking that does not blindly accept arguments and conclusions. It examines assumptions, discerns hidden values, evaluates evidence, and assesses conclusions.
  
  

Module 5: Scientific Method and Description

How Do Psychologists Use the Scientific Method to Study Behavior and Mental Processes?

Curiosity: Sample Questions

• Does participation in sports improve grades?
  
  

• Does caffeine improve mental acuity?
  
  

• Is musical taste an indicator of intelligence?
  
  

• Does texting diminish interpersonal communication?
  
  

Terms to Know

• Hypothesis: A testable prediction often implied by a theory.
  
  

  • Alternate: A statement of difference.
    
    

  • Null: A statement of NO difference.
    
    

• Theory: An explanation using an integrated set of principles that organizes observations and predicts behaviors and events.
  
  

Law vs. Theory vs. Hypothesis

• Law: A general statement describing some pattern in nature that holds without exception under specified conditions.
  
  

• Theory: A hypothesis that has been tested and supported many times. Serves as a basis for describing observed patterns.
  
  

• Hypothesis: A possible answer to a question.
  
  

Operational Definitions

• A statement to describe the procedures used to define/measure the research variables (DV and IV) of a study.
  
  

Necessity of Operational Definitions

• Allow for appropriate analysis of statistical findings.
  
  

• Facilitate peer review.
  
  

• Allow for replication—repeating the essence of a research study, usually with different participants in different situations to see whether the basic finding extends to other experiments.
  
  

Types of Research

• Descriptive: Gathering information pertaining to the research question.
  
  

• Correlation: Does a relationship exist between two variables?
  
  

• Experiments: Is there a causal relationship between two variables?
  
  

The Case Study

• In-depth study of one person or a small group.
  
  

• Utilizes observation, testing, interviews, etc.
  
  

• Popular with Freud and Piaget.
  
  

Strengths

• Allows study of infrequent or non-replicable subjects.
  
  

• Provides detailed description.
  
  

Weaknesses

• Observer bias.
  
  

• Inability to generalize to larger populations.
  
  

Example: Anna O. (Bertha Pappenheim)

• Patient of Josef Breuer.
  
  

• Fell ill during her father's illness and death.
  
  

• Symptoms: cough, blurred vision, hallucinations, partial aphasia, loss of use of her left side.
  
  

• Treated using the "talking cure," which became the foundation of Psychoanalysis.
  
  

• Her illness continued after treatment.
  
  

Naturalistic Observation

• Systematic observation of an organism in its natural setting.
  
  

Strengths

• Behavior is not influenced by an artificial environment.
  
  

• Data gathered at the time of the event.
  
  

Weaknesses

• Observer bias.
  
  

• Observer influence (effect).
  
  

• Inability to generalize to other populations.
  
  

Basic vs. Applied Research

• Basic Research: Seeks answers for the sake of increasing knowledge.
  
  

• Applied Research: Seeks answers for specific problems.
  
  

The Survey

• Collecting self-reported attitudes, opinions, or behaviors, usually by questioning a representative, random sample.
  
  

Strengths

• Cheap, large reach, quick, and easy.
  
  

Weaknesses

• Self-reports may be inaccurate or fabricated.
  
  

• Question wording can influence results.
  
  

• Sampling errors can skew data.
  
  

Correlation

• Measures the relationship between two factors; allows prediction of one from the other.
  
  

• Correlation Coefficient: Ranges from -1 to +1 (Pearson’s r).
  
  

  • Closer to +1: Stronger positive relationship.
    
    

  • Closer to -1: Stronger negative relationship.
    
    

• CORRELATION DOES NOT IMPLY CAUSATION
  
  

Scatterplots

• Graph of plotted data points showing the relationship between two variables.
  
  

• Slope suggests direction (positive/negative).
  
  

• Scatter suggests strength of relationship (r).
  
  

Direction of Relationship

• Positive Correlation: Both variables rise/fall together.
  
  

• Negative Correlation: One variable rises, the other falls.
  
  

Illusory Correlations

• Perceived but nonexistent relationship.
  
  

• We notice and recall events that support our beliefs.
  
  

• Explains superstitious beliefs.
  
  

Perceiving Order in Random Events

• We tend to look for meaningful patterns, even when none exist.
  
  

Experimentation

• Only method to determine cause and effect.
  
  

Components of an Experiment

• Participants: Subjects.
  
  

• Variables: Factors that can vary.
  
  

• Operational Definitions: Procedures used to measure variables.
  
  

Key Variables

• Independent Variable (IV): Manipulated; the cause.
  
  

• Dependent Variable (DV): Measured; the effect.
  
  

Problems to Watch For

• Confounding Variables: Uncontrolled factors influencing the DV.
  
  

• Experimental Bias: Unintentional influence from the experimenter.
  
  

• Experimental Group: Receives treatment.
  
  

• Control Group: No treatment, same in all other ways.
  
  

• Random Assignment: Randomly assigning participants to minimize differences.
  
  

• Placebo: Fake treatment for control group.
  
  

• Placebo Effect: Results caused by expectation alone.
  
  

• Single Blind Study: Participants unaware of their group.
  
  

• Double Blind Study: Both participants and experimenters are unaware.
  
  

Example Setup

• Participants: White mice.
  
  

• IV: Protein in the seeds.
  
  

• DV: Mass of each mouse.
  
  

• Operational Definition: 300 mice, same age/weight, split into groups.
  
  

Statistical Reasoning

• Statistics help analyze and interpret data.
  
  

• Misrepresented data can lead to false conclusions.
  
  

Measures of Central Tendency

• Mean: Average.
  
  

• Median: Middle score.
  
  

• Mode: Most frequent score.
  
  

• Bimodal/Multimodal: Data sets with more than one mode.
  
  

Measures of Variability

• Range: Highest score minus lowest.
  
  

• Standard Deviation: Dispersion of scores around the mean.
  
  

Making Reliable Generalizations

• Use a representative sample.
  
  

• Ensure large sample size.
  
  

• Look for less variable data.
  
  

Statistical Significance

• Determines if differences between group means are due to real effects or chance.
  
  

• Less than 5% due to chance (p < 0.05).
  
  

Testing for Differences

• Chi Square: Relationship between variables.
  
  

• T Score: Probability that group differences are due to chance.
  
  

Ethical Guidelines: With Humans

1. Benefits outweigh the risks.
   
   

2. Minimize risks.
   
   

3. Protect welfare and dignity.
   
   

4. Follow state/federal laws.
   
   

5. Informed consent.
   
   

6. Deception only if justified; must debrief.
   
   

7. Right to withdraw.
   
   

8. No mental/physical harm.
   
   

9. Repair any harm caused.
   
   

10. Confidentiality.
    
    

11. Debrief participants on purpose/findings.
    
    

Ethical Guidelines: With Animals

1. Treat animals humanely.
   
   

2. Follow state/federal laws.
   
   

3. Trained psychologists supervise.
   
   

4. Minimize pain/discomfort.
   
   

5. Use proper anesthesia/sterilization.
   
   

6. If necessary, euthanize quickly and painlessly.