Psychology Research Methods Lecture 1 & 2

Lecture 1: Generating Models

• A theory is a formal model for explaining a phenomenon and predicting related outcomes.
• It should explain "how," "why," and "under what conditions" phenomena occur.
• Parsimony is the principle of the simplest explanation.
• William of Ockham's principle states that a theory should contain no more complexity than necessary.
• The scientific process typically involves: defining the problem, determining variables, selecting a research design/sample, collecting data, analyzing, and interpreting the findings.
• A research problem presents a broad statement identifying a significant area needing investigation, a gap, or controversy.

Basic vs Applied Research

• Basic research addresses fundamental questions about behavior.
• Applied research tests if variables relate to one another under specific conditions.

Lecture 2: Measurement

• Variables are behaviors, thoughts, feelings, or characteristics that vary.
• Measurement assigns numerical values to variables.
• Conceptual variables are the phenomenon of interest (e.g., intelligence).
• Operational variables define how constructs are measured or manipulated in research (e.g., an IQ test).
• Objective measures are "hard" data (e.g., sales figures).
• Subjective measures rely on perception (e.g., self-report).

Explicit vs Implicit Measures

• Explicit measures assess conscious processes, such as self-report.
• Implicit measures assess unconscious processes, such as reaction time.

Common Rating Techniques

• Likert scales measure agreement levels.
• Semantic differentials use bipolar adjectives.
• Frequency scales count occurrences.
• Pain charts, checklists are other examples.

Scales of Measurement

• Nominal scales categorize objects (e.g., gender).
• Ordinal scales rank objects (e.g., education level).
• Interval scales quantify intervals (e.g., temperature).
• Ratio scales capture intervals and have a true zero point (e.g., reaction time).

Validity and Reliability

• Reliability assesses consistency, while validity assures measurement accuracy.
• Test-retest reliability measures the consistency of a test over time, parallel-form reliability examines the consistency of different but similar forms of a test, and inter-rater reliability measures the agreement between multiple raters.
• Internal consistency measures how consistently items on a single instrument measure the same construct.

Lecture 3: Sampling

• A population is a group defined by research interests.
• A sample is a subset of the population used for data collection.
• Census collects data from the entire population.
• Sampling involves selecting a subset for research.
• The goal is to create a sample representative of the population for valid generalization.
• Probability sampling methods include random sampling, stratified sampling, and cluster sampling.
• Non-probability sampling Methods include convenience sampling, snowball sampling, quota sampling, and judgmental sampling.

Lecture 4: Qualitative and Observational Methods

• Observational research involves directly observing phenomena without manipulation.
• Naturalistic observation involves observing subjects in their natural environment.
• Systematic observations use a coding scheme to record specific behaviors.
• Indirect observations involve observing outcomes (e.g., recycling rate).

Qualitative Data Analysis

• Thematic analysis identifies themes from qualitative data.
• Grounded theory develops theory from data.
• Content analysis quantifies qualitative data.

Lecture 5: Experimental Methods

• Experiments involve manipulating independent variables (IVs) to assess their impact on dependent variables (DVs).
• True experiments utilize random assignments, while quasi-experiments don't.
• Manipulation checks verify the effect of the IV.
• Control groups provide comparisons, while extraneous variables (confounds) threaten internal validity, meaning factors besides the IV may influence the DV.

Realism

• Experimental realism examines if psychological states are experienced by participants in a study.
• Mundane realism assesses if study elements simulate real-world situations.

Lecture 6: Survey Methods

• Survey methods operationalize constructs using items, analyze responses, and examine validity/reliability.
• The methods need to accurately and fully reflect the intended measure, so items should be valid, reliability should be acceptable and they should avoid common method variance, which is a threat to validity since variables are measured in the same way.

Lecture 7: Evaluating Research

• Construct validity measures whether a measure accurately and adequately represents the construct.
• Internal validity ensures that the observed relationship between variables is not due to extraneous factors.
• External validity assesses the extent to which the findings are generalizable to other populations, settings, and times.

Lecture 8: Threats to Validity

• Regression to the mean occurs when participants are selected based on extreme scores, and subsequent scores revert to the average.
• Instrumentation refers to a change in the measurement instrument or person being measured, rather than the effect of the IV on the DV.
• External validity assesses whether the causal relationship from a study is valid in other populations, contexts, times, and behaviors being measured.

Ethical Principles in Research

• Research should be conducted ethically, ensuring equal benefits and burdens, protecting vulnerable populations, providing informed consent, and avoiding deception whenever possible.

Lecture 9: Alternative and Emerging Methods

• Work samples provide realistic simulations of job tasks.
• Fidelity reflects the similarity between the work samples and job contexts.
• Response fidelity considers if participants respond similarly in the sample and target contexts.

Lecture 10: Experience Sampling Method (ESM)

• Experience sampling is a survey methodology for capturing experiences in real-time.

Lecture 11: Meta-Analysis

• Meta-analysis is a quantitative method for evaluating multiple studies