Research Methods in Social Psychology

Defining Social Psychology and Subjective Experience

• Social Psychology Definition: According to Allport (1985), social psychology is defined as "the scientific study of how people’s thoughts, feelings, and behaviors are influenced by … others."

• Bi-directional Influence: The field investigates how others influence an individual and, conversely, how the individual influences others.

• Example of Influence: The Milgram Studies provide a classic example of influence, specifically focusing on obedience to authority.

• Subjective Experience: Social psychology is characterized as the science of subjective experience (Balcetis & Dunning, 2010).

• The Core of the Field: A fundamental premise is that many things in the world are inherently ambiguous. Consequently, our perception, interpretation, and memory of these things are heavily influenced by our personal:     - Needs     - Wishes     - Expectations

The Requirements of Scientific Procedure

• Determining Science: To evaluate if a claim is scientific rather than pseudoscience, intuition, or logical debate, one must examine the method. The quality of a scientific claim is also rooted in its methodology.

• Core Requirements: For a method to be considered scientific, it must investigate the world in a way that satisfies four specific requirements:     - Objectivity: This is the ability of something to be observed by a third party. For example, people’s beliefs in horoscopes are objective (they can be measured), but the "unmeasurable connection between an astrologer and the stars" is not.     - Verifiability: This asks, "Can I find results that indicate, 'yes, I am correct'?" Results are verifiable when outcomes are measurable. Claims that do not generate testable hypotheses fail this criterion.     - Falsifiability: This asks, "Can I find results that indicate: 'No, I am not correct'?" The key is determining what it would take to prove a claim wrong. If nothing can show a claim is wrong (e.g., "I know I'm right"), science cannot address it. Pseudoscience, faith, and conspiracy theories often lack falsifiability.     - Repeatability: This requires that the procedure be recorded and that it can be replicated by someone else at a later time.

The Five Steps of the Scientific Method

1. Hypothesize: State the specific phenomenon or relationship you want to investigate.

2. Operationalize: Define specifically what you are interested in measuring by making variables concrete and observable.

3. Manipulate and Measure: Conduct the study using the appropriate procedures and materials to collect data.

4. Evaluate: Analyze the gathered data to determine if the findings are valid and if they support the hypothesis.

5. Revise or Replicate: Based on the results, determine what changes should be made to the study or repeat the study to confirm the findings.

Hypotheses and Theories

• Variable: Defined as anything that can potentially hold more than one value.     - Examples of Variables: Weather, ice cream flavor, or the number of chocolate ice cream scoops on a waffle cone.

• Hypothesis Criteria: A prediction about the relationship between variables or the amount of a single variable. It must:     - Involve at least one variable.     - Have measurable variables (Objectivity).     - Be verifiable (Testable).     - Be falsifiable.     - Be repeatable.

• Hypothesis Example: "Social distancing reduces COVID-19 transmission."

• Theory: Defined as an organized set of principles that explain phenomena. Theories are broad, whereas hypotheses are specific and directly testable.

• The Relationship between Theory and Hypothesis: Hypotheses are driven by theory.     - Theory Example: "Pathogens can be transmitted through close human contact."     - Theory Example: "Advertising makes people like and buy products."     - Hypothesis derived from Theory: "This commercial will persuade people to go to the theater."

Operationalization: From Concepts to Measurement

• Goal: Making a conceptual variable concrete and measurable to ensure objectivity.

• Conceptual Definition: A broad, unmeasurable abstraction used to describe an idea (e.g., "Social Distancing", "Aggression", "Happiness").

• Operational Definition: A specific, observable, and concrete measurement (e.g., "The distance at which people imagine placing themselves from others within virtual scenarios").

• Examples of Operationalizing Aggression:     - Decibels of volume in yelling.     - Number of curse words spoken in $60\,\text{minutes}$.     - Muscle tension measurements.     - Randomly assigning people to listen to "screamo" music versus Vivaldi.     - Rating on a $1$ to $10$ scale: "How aggressive are you?"

• Examples of Operationalizing Happiness and Helping:     - Conceptual: Happiness; Operational: Mood scale or listening to happy music.     - Conceptual: Helping; Operational: Volunteer work, donating to charity, or picking up dropped items.

Types of Research Designs

• Observational / Descriptive Research:     - Purpose: To identify if something exists and how often it occurs.     - Method: Observing in the field, the laboratory, or using historical records.     - Variable Limit: Central interest is usually only on ONE variable. If TWO or more are involved, it becomes correlational or experimental.     - Note: This is not just any "observation," as all science involves observation.

• Correlational Research:     - Purpose: Examines the relationship between two or more variables. It asks, "Does $x$ change when $y$ changes?"     - Language: Predicts, associated with, related, linked, connected.

• Experimental Research:     - Purpose: Manipulates one variable to see its effect on another variable to determine cause and effect ($x$ causes $y$).

Correlational Research and Pearson’s r

• Pearson’s r: A statistic indicating the size and direction of the relationship between two variables. The value ranges from $-1$ to $+1$.     - Positive Correlation: As $x$ increases, $y$ increases ($r$ approaches $+1$). Example: Shoe size and height, where $r \approx 0.9$.     - Negative Correlation: As one variable increases, the other decreases ($r$ approaches $-1$). Example: As computer age increases, efficiency decreases ($r \approx -0.9$).     - Zero Correlation: The value of one variable is unrelated to the other ($r = 0$). Example: Math ability and love for pickles.

• The Third Variable Problem: Correlation does not equal causation because an unmeasured third variable might be causing both.     - Example: Cities with more bars have more churches. The third variable is the population size.     - Example: Shark attacks and ice cream consumption are correlated because of a third variable (warm weather/summer).     - Additional Examples: Vitamin intake being linked to health; executives saying "please" and "thank you" linked to business success; air pollution linked to autism.

Experimental Research: The Gold Standard

• Key Components:     - Independent Variable (IV): The variable that is manipulated; considered the "cause."     - Dependent Variable (DV): The variable that is measured; considered the "effect."

• Experimental Control: To ensure the IV caused the DV, scientists control everything except the measured outcome, including:     - Materials     - Time and Place     - Personnel and Experimenter behavior     - Avoiding demand effects

• Random Selection: Obtaining a sample from the population where every individual has an equal chance of being chosen.

• Random Assignment: Assigning participants to different conditions (e.g., Experimental vs. Control) randomly. This is the mechanism that allows scientists to overcome the third-variable problem and determine true cause and effect.

Evaluation, Revision, and Replication

• Evaluation: Analyzing data to test predictions.

• Validity: The degree to which the study accurately tested the hypothesis.

• Revision: Fixing problems with study design or altering the hypothesis if results do not support it.

• Replication: Redoing the study to see if similar results occur in new situations. This is necessary even if results support the hypothesis to ensure the findings hold up over time.

Case Study: Eye Contact and Love (Flawed Study)

• Hypothesis: Eye contact leads to romantic love.

• Method: $500$ randomly selected married couples play a board game for $1\,\text{hour}$. Eye contact is observed. Love is measured on a $0$ to $10$ scale.

• Findings: r = 0.75, p < .001.

• Flaw in Conclusion: The researchers concluded eye contact caused love. However, because this was an observational/correlational design (not manipulating eye contact), they cannot determine causation. It is just as likely that being in love causes more eye contact.

• Operationalization Minor Flaw: A one-item self-report scale may not fully capture the complexity of "romantic love."

Case Study: Extrasensory Perception (Bem, 2011)

• Context: Daryl Bem investigated precognition (awareness of future events).

• Method: Participants chose between two curtains on a computer screen. Behind one was a picture; behind the other was a blank wall. Some pictures were erotic.

• Hypothesis: Participants would identify the position of erotic pictures significantly more often than chance ($50\%$).

• Findings: Participants were accurate $53\%$ of the time for erotic images, which was statistically robust and replicated nine times. Non-erotic images were identified at chance levels.

• Controversy: $34\%$ of academic psychologists considered precognition "completely impossible."

• Scientific Integrity Questions:     - If a psychologist refuses to examine the study because they "know" it's impossible, they violate the requirement of Falsifiability.     - If Bem uses the study only to support existing "knowledge" that ESP is real, he violates the requirement of Objectivity.

Practice Items & Classroom Discussion

• Question on Correlation: A correlation of $r = .45$ between violent TV and aggression indicates that as TV viewing increases, aggressive behavior increases. (This does not prove causation).

• Question on Objectivity: Which hypothesis is least objective? "People's social behaviors are influenced by unconscious processes that no measurement can detect." (Because it cannot be observed/measured).

• Experimental Identification: A study measuring help-seeking behavior in a room filling with smoke is an Observational/Descriptive study if there is no manipulation or comparison of variables.

• Field Study Identification: Michelle measuring smiles in parks vs. grocery stores is conducting a Correlational study (comparing two existing environments) or an Observational study depending on the specific analysis.

Questions & Discussion

• Exam Logistics: Exams will cover only the material presented in lecture. The textbook is intended as a supplement.

• Administrative Note: For PSYCH 1375 with Dr. Lee, the room has moved to Hitchcock Hall 324.

• Next Class Task: Students are asked to design three types of studies (Observational, Correlational, Experimental) based on the theory: "Happiness can cause people to help others."     - Operationalization requirement: Clearly define how "Happiness" and "Helping" will be measured in each design.

• Types of Research Designs:

  • Observational/Descriptive Research: Identifies the existence and frequency of a phenomenon.

  • Correlational Research: Examines relationships between variables.

  • Experimental Research: Manipulates one variable to determine cause-and-effect.

• Pearson’s r: Measures the size and direction of relationship between two variables; ranges from $-1$ to $+1$.

  • Positive correlation: As one variable increases, so does the other.

  • Negative correlation: As one variable increases, the other decreases.

  • Zero correlation: No relationship between the variables.

• Experimental Control: Ensures only the independent variable affects the dependent variable by controlling all else.

• Random Assignment: Participants are randomly assigned to conditions to eliminate third-variable issues.

• Validity: Degree to which the study accurately tested the hypothesis.

• Replication: Important for confirming findings over time by repeating the study in different contexts or conditions.

• Practical Examples: Use case studies or examples to illustrate theoretical concepts (e.g., eye contact related to love or precognition studies).