Chapter 2 Notes: Psychological Research
Why it matters
Historically, people believed essential claims like: Earth is flat and mental illness is demonic possession.
Why study psychology scientifically? Research is necessary for validating claims; otherwise intuition and baseless assumptions may mislead.
Science requires a systematic process and verification of findings.
Trephination example: Some ancestors believed that making a hole in the skull would let evil spirits leave the body, curing mental illness and other disorders. (Figure 2.2; credit: taiproject/Flickr)
Reasoning in the research process
Deductive reasoning
Results are predicted based on a general premise.
Example (logical):
All living things require energy to survive (premise)
Humans are living things (premise)
Therefore, humans require energy to survive (conclusion)
Based on logical analysis.
Inductive reasoning
Conclusions are drawn from observations (empirical).
Example (empirical):
Humans require energy to survive
Dogs require energy to survive
Trees require energy to survive
AI programs require energy to run
Conclusion: AI must be a living thing
Science uses both forms of reasoning
Ideas are formed through deductive reasoning.
Hypotheses are tested through empirical observations.
Scientists form conclusions through inductive reasoning.
Conclusions lead to new theories, which generate new hypotheses, continuing the cycle.
Key terms
Theory: a well-developed set of ideas that proposes an explanation for observed phenomena.
Hypothesis: a tentative and testable statement about the relationship between two or more variables.
Predicts how the world will behave if the theory is correct.
Usually an “if-then” statement: \text{If } X \text{, then } Y.
Is falsifiable (capable of being shown to be incorrect), usually using empirical methods.
Types of Research
Not all research is experimental.
In this class:
1) The term “experiment” describes a very particular type of research design.
2) “Empirical”: researchers followed a methodology and collected their own data to observe, analyze, and describe.
Case studies
Case studies focus on one individual.
The studied individual is typically in an extreme or unique psychological circumstance.
Classic example: Phineas Gage.
Conclusions: Brain injury (frontal lobe) might impact behaviors related to personality, but generalizing should be done with CAUTION.
Pros (PRO): Allows for rich insight into a case.
Cons (CON): Difficult to generalize results to the larger population.
Naturalistic observation
Naturalistic observation = observation of behavior in its natural setting.
Pros (PRO): Eliminates performance anxiety; allows study of genuine behaviors.
Cons (CON): Observer bias; observations may be skewed to fit expectations.
Observer bias: bias in observations due to observer expectations.
Establishing clear criteria for observation helps reduce observer bias.
Example: Seeing a police car behind you may alter driving behavior. (credit: Michael Gil)
Surveys
A survey is a list of questions delivered in multiple formats: paper-and-pencil, electronic, or verbal.
Used to gather a large amount of data from a sample (subset of individuals) from a larger population.
Pros (PRO): Efficiently collects data from many people.
Cons (CON): People may lie; less depth per respondent.
Quantitative vs. Qualitative data.
Archival research
Uses past records or data sets to answer research questions or identify patterns/relationships.
Pros (PRO): Data are already obtained, saving time and money.
Cons (CON): Cannot change what information is available.
Researchers examine records, whether hardcopy or electronic.
(credit: paper files; computer archives)
It’s all about the timing
Cross-sectional research: comparing multiple groups at a single point in time.
Longitudinal research: multiple measurements from the same group over time.
Risk of attrition: participants dropping out over time.
Correlations
Correlation: relationship between two or more variables; when two variables are correlated, one variable changes as the other does.
Correlation details
Correlation Coefficient: a number from -1 to +1, indicating the strength and direction of the relationship, usually represented by r.
The more the data align with a straight line (points close to a line), the stronger the correlation.
Positive correlation: variables change in the same direction (both increase or both decrease).
Negative correlation: variables change in opposite directions (one increases, the other decreases).
Scatterplots visually display the strength and direction of correlations.
Stronger correlations have data points lying closer to a straight line.
Correlation DOES NOT mean causation
Cause-and-effect relationship: changes in one variable cause changes in the other; can be established only through experimental design.
Confounding variable: an outside factor that affects both variables, creating a false impression of causality.
Example: Ice cream sales and drowning incidents can both rise with hot weather, suggesting a spurious relationship.
Issues with correlational research
Illusory correlations: perceiving a relationship where none exists.
Confirmation bias: tendency to ignore evidence that contradicts beliefs.
Example: The full moon belief that it affects behavior; research shows no reliable relationship.
Cause-and-effect
Can be conclusively established only with an experiment.
Not all research counts as an “experiment.”
Experiments involve:
Experimental group: participants who experience the manipulated variable.
Control group: participants who do not experience the manipulated variable; used for comparison and to control for chance factors.
Example experiment
Participants are randomly assigned to the control or experimental group (random assignment is the key difference).
Example: Bystander effect
Experimental group: confederates (fake participants) present.
Control group: no other people around.
Research question: How does the presence of others impact how people interpret an emergency?
Operational definitions: precise definitions of what is being studied and how it will be measured.
Example: interpretation of emergency, measured by whether participants act in response to the emergency.
Other experimental design considerations
Aim to minimize bias and placebo effects.
Experimenter bias: researchers’ expectations skew results.
Participant bias: participants’ expectations skew results (e.g., placebo effect, power of expectations).
Solution: Blinding.
Single-blind: participants do not know which group they’re in.
Double-blind: neither participants nor researchers who interact with participants know group assignments.
What are we studying?
Variable: a characteristic on which subjects can vary.
Independent variable (IV): something researchers directly control in an experiment (e.g., which group).
Dependent variable (DV): something measured that may be influenced by the IV.
Selecting participants
Participants are recruited from a population into a smaller subset called a sample.
Random sampling is the “gold standard” → ensures representation and minimizes bias.
Goal: use a sample of a population to generalize findings to the population.
What do the results say?
Data are analyzed with statistics to determine whether results could have occurred by chance (a random fluke) rather than due to the study itself.
Statistical significance: when results are very unlikely to have occurred by chance, typically defined as p < 0.05.
Reporting the findings
Scientific studies are typically published in peer-reviewed journals.
Other scientists with knowledge on the topic review the study for quality and impact.
Feedback contributes to quality control and improvement of research.
Recognizing good science
Measures and results should be:
Reliable: consistent over time and across situations, raters, or observers.
Valid: measuring what the study intends to measure.
Variable vs. Operational Definitions:
A valid measure is always reliable, but a reliable measure is not always valid.
Ethics in research
Ethical principles are enforced by review boards/agencies.
Human subjects research: Institutional Review Boards (IRBs).
Check for informed consent: voluntary agreement to participate after knowing the procedures, risks, benefits, implications, and confidentiality assurances.
Check for risks vs. benefits to participants.
Animal subjects research: Institutional Animal Care and Use Committee (IACUC).
Check for humane treatment of animals.
Additional ethical considerations include confidentiality, minimizing harm, and voluntary participation.