Empiricism, Rationalism, and Research in Psychology
Empiricism and Rationalism in Psychological Research
Empiricism emphasizes quantitative evidence in the study of perception, cognition, and personality. Rationalism uses logic, such as: if A>B and B>C, then A>C. Theories are not definitively proven; they require ongoing experimentation.
Goals of Research in Psychology
- Describe Behavior (Frequency Claims):
- Identify regularly occurring sequences of events.
- Classify behaviors.
- Quantify behaviors precisely.
- Predict Behavior (Association Claims):
- Identify relationships between variables.
- The strength of the relationship determines the confidence in prediction (e.g., violent media predicts real-world violence).
- Explain Behavior (Causal Claims):
- Understand cause-and-effect relationships.
- Develop and test theories about why phenomena occur (e.g., higher testosterone levels may influence violence).
Valid logic means true premises always lead to a true conclusion. Sound logic means the argument is valid and all premises are true.
Example of Valid and Sound Logic:
- I am a man.
- All men are mortal.
- Therefore, I am mortal.
Rationalism: Inductive and Deductive Reasoning
- Inductive Reasoning: Reasoning from specific cases to general principles (probably true).
- Deductive Reasoning: Reasoning from general principles to specific conclusions (guaranteed true if premises are true).
- Example: All men are mortal. Bob is a man. Therefore, Bob is mortal.
- Modus Ponens (Affirming): All fruits contain seeds. An apple is a fruit. Therefore, apples contain seeds.
- Modus Tollens (Denying): All fruits contain seeds. Carrots do not contain seeds. Therefore, carrots are not fruits.
Deductive Fallacies/Errors
- Denying the Antecedent: All fruits contain seeds. Eggplant are not a fruit. Therefore, eggplant do not contain seeds (Incorrect).
- Affirming the Consequence: All fruits contain seeds. Acorns contain seeds. Therefore, acorns are a fruit (Incorrect).
- Incorrect Premise: All birds fly. Penguins are birds. Therefore, penguins can fly (Incorrect).
Empiricism in Research
- Systematically gather data to answer questions.
- Reduce subjectivity.
- Be open to accepting data findings.
- Use appropriate control or comparison groups.
Characteristics of a Good Theory
- Consistent with known facts.
- Logically consistent.
- Parsimonious (simple).
- Testable and falsifiable (there must be a possible outcome that could disprove the hypothesis).
- Precise enough to be disproven.
- Example: Yerkes-Dodson Law – If stimulus strength increases sufficiently, the rate of correct responses will decline.
Types of Hypotheses
- Directional Alternative Hypothesis:
- Group 1 will perform better than Group 2.
- As X increases, Y increases.
- As X increases, Y decreases.
- Causal Hypotheses:
- Define a causal relationship.
- The experimenter controls the cause.
- “If I change X, then Y will change.”
- Requires co-occurrence, time sequence, and ruling out alternative causes.
- Associative Hypotheses:
- Describe associations and predict outcomes.
- The experimenter does not control either variable.
- “These groups respond differently.”
Module 1 Summary
- Scientific knowledge combines rationalism (inductive and deductive reasoning) and empiricism (collecting unbiased data).
- Theories should be parsimonious, consistent, testable, and falsifiable.
- Hypotheses are testable (falsifiable) statements, including null, alternative, and directional hypotheses.
Variables and Claims in Psychological Research
Understanding Variables
- Operational Definitions: Defining variables by the methods used to measure them.
- Categorical and Continuous Variables:
- Categorical: Vary in kind (e.g., gender).
- Continuous: Vary in amount (e.g., time in milliseconds).
- Levels/Values: Different values a variable can take.
- Predictor and Outcome Variables:
- Predictor (Independent/Participant): The variable that is manipulated or used to classify subjects.
- Outcome (Dependent): The variable that is measured.
Measuring Variables
- Behavioral: Directly observe behavior (e.g., multiple-choice test performance).
- Self-Report: Ask participants to report (e.g., attitudes, beliefs).
- Physiological: Monitor biological responses (e.g., EMG, MRI).
Types of Claims
- Frequency Claims: Describe behavior.
- Association Claims: Identify relationships between variables.
- Causal Claims: Determine cause-and-effect relationships.
Associations Between Variables
- Positive Linear Association: Increases in one variable relate to increases in another.
- Negative Linear Association: Increases in one variable relate to decreases in another.
- Curvilinear Association: Increases in one variable relate to both increases and decreases in another.
- No Association: No systematic relationship between variables.
Criteria for Causal Relationships
- Co-Occurrence: Cause and effect must both occur or neither occur.
- Time Sequence: The cause must precede the effect.
- Alternative Causes: Must be ruled out.
Correlational vs. Experimental Research
- Correlational Research: Two measured variables; searches for association (cannot assess causal claims).
- Experimental Research: One manipulated variable, one or more measured variables; searches for causation.
Important: There is no overall “best” method; the research question drives the methodology. Scientists are skeptical and require replication of findings.
Reliability, Validity, and Measurement Scales
Measuring Variables
- Consistency (Reliability): The extent to which a measure yields consistent results.
- Accuracy (Validity): The extent to which a measure accurately reflects the construct.
Types of Validity
- Construct Validity: How well the variables are measured.
- Face Validity: Does the measure appear to assess the construct?
- Concurrent and Predictive Validity: Does the measure correlate with present and future performance?
- Convergent and Divergent Validity: Does the measure relate appropriately to other measures?
- Internal Validity: Do the conclusions follow logically from the study?
- External Validity: Do the results generalize to other situations and people?
- Statistical Validity: Avoid Type I (false positive) and Type II (false negative) errors.
Measuring Reliability
- Test-Retest: Consistency over time.
- Split-Half: Consistency within the measure.
- Parallel/Alternate Forms: Consistency across different versions of the measure.
- Item-Total Correlation: Consistency between individual items and the total score.
- Coefficient Alpha (Cronbach’s): Overall internal consistency (>.7 is good).
Scales of Measurement
- Nominal: Categories with no inherent order (e.g., male/female).
- Ordinal: Categories with a meaningful order (e.g., 1st, 2nd, 3rd).
- Interval: Equal intervals between values, but no true zero (e.g., IQ scores).
- Ratio: Equal intervals and a true zero point (e.g., weight, exam scores).
Continuous: Ratio, Interval
Categorical: Ordinal, Nominal
Abstract Number System
- Identity: Each number has a particular meaning.
- Magnitude: Numbers have an inherent order.
- Equal Intervals: The difference between units is constant.
- True Zero: Zero indicates the absence of the variable.
Ethics in Human and Animal Research
Ethical Considerations
- Why Ethics Matter: Historical abuses (e.g., Milgram’s Obedience Experiment) highlight the need for ethical guidelines.
- Safeguards:
- The Belmont Report (1976) and APA Ethical Principles (2002) for human research.
- Guide for the Care and Use of Laboratory Animals (2011) for animal research.
- Enforcement:
- Institutional Review Board (IRB) for human subjects.
- Institutional Animal Care and Use Committee (IACUC) for animal subjects.
Participant Rights
- Voluntary Participation: Subjects can stop at any time.
- Informed Consent: Participants must know the risks and benefits.
- Confidentiality: Protect participants’ identities.
- Deception: Only justified if benefits outweigh risks; requires debriefing.
- Debriefing: Inform participants of the true purpose and get feedback.
Locating Published Research
- Use library and internet databases.
- Books and Book Chapters: Provide overviews, sometimes peer-reviewed.
- Scientific Journals: Always peer-reviewed, include empirical studies and review articles.
Elements of APA Style
- Strive for accuracy, brevity, and clarity.
- Use unbiased language.
- Use active voice and past tense.
- Proper referencing in text and reference list.
Parts of a Journal Article (APA Style)
- Title Page: Title, author names, affiliations, running head, author’s notes.
- Abstract: 100-200 word summary.
- Introduction: Establishes importance, describes current understanding, states hypothesis.
- Methods: Participants, materials, procedures, statistical analysis.
- Results: Descriptive and inferential statistics, tables, and graphs.
- Discussion: Interpretation, evaluation of hypothesis, alternative explanations, critique, and broader implications.