Methods of Enquiry in Psychology - Study Notes

Psychological research aims to:
• Describe behaviour and mental processes.
• Predict future occurrences.
• Explain underlying mechanisms.
• Control or modify behaviour when appropriate.
• Apply knowledge in an objective, evidence-based manner.
Two complementary orientations:
• Objective, generalisable laws discovered via controlled, empirical methods.
• Subjective, context-bound meanings understood through qualitative interpretation of lived experience.

Conceptualising a problem → formulating precise research questions & hypotheses.
Selecting an appropriate method & collecting data.
Analysing data (quantitative and/or qualitative).
Drawing conclusions; revising theories, hypotheses, or methods as needed.
Communicating findings; integrating with existing literature and real-world issues.

Demographic: age, gender, SES, education, cultural background.
Environmental: situational factors such as classroom climate, noise, temperature.
Physical/physiological: heart rate, galvanic skin response, cortisol levels.
Psychological: attitudes, beliefs, cognitive scores, emotional states.
All data are located in a specific context and interpreted relative to the theory and measurement technique used.

Descriptive methods (surveys, naturalistic observation, clinical observations) → goal of description.
Correlational methods → goal of prediction.
Formal experiments → goals of explanation (cause → effect) and behavioural influence.

Definition: systematic, organised, objective recording of naturally occurring behaviour in real time.
Forms:
• Naturalistic vs. Controlled (laboratory) settings.
• Participant vs. Non-participant roles for the researcher.
Strengths: ecological validity, rich contextual data, useful for hypothesis generation.
Limitations: potential observer bias, reactivity (participants alter behaviour), difficulties inferring causality.

Purpose: establish causal relationships.
Core structure:
• Independent variable (IV) → deliberately manipulated.
• Dependent variable (DV) → measured outcome.
• At least one Experimental Group (receives IV) & one Control Group (baseline).
Causal inference: significant DV differences between groups attributed to IV if confounds are controlled.
Types:
• Laboratory experiments (high control, possible lower ecological validity).
• Field experiments (natural setting, moderate control).
• Natural/Quasi experiments (researcher lacks full random assignment; utilises naturally occurring variations).
Example causal chain: manipulating sleep duration (IV) to test effect on working-memory accuracy (DV).

Examines degree & direction of association between two variables.
Correlation coefficient $r$ ranges $-1.00 \le r \le +1.00$ .
• Positive correlation: variables increase/decrease together (e.g., study hours & GPA).
• Negative correlation: one increases while the other decreases (e.g., stress & immune functioning).
• Zero correlation: no linear relation.
Strengths: can study variables that cannot be ethically or practically manipulated; basis for prediction.
Limitations: cannot demonstrate causation (directionality & third-variable problems).

Goal: obtain self-reported data about attitudes, behaviours, or demographics to describe “what is.”
Instruments:
• Questionnaires (paper, online): inexpensive, scalable, can assure anonymity.
• Interviews (structured, semi-structured, unstructured): face-to-face flexibility, richer data, higher cost.
• Telephonic surveys: compromise between reach and depth.
Design considerations: sampling strategy, wording clarity, order effects, response biases (social desirability).

In-depth exploration of a single individual, group, organisation, or event.
Data sources triangulated: observation, archival documents, interviews, psychological tests.
Contributions: generate new hypotheses, illustrate rare phenomena (e.g., brain injury and language).
Cautions: limited generalisability, potential researcher/participant biases.

Definition: standardised, objective instruments that quantify individual differences relative to norms.
Desired psychometric properties:
• High Reliability (consistency across time, items, scorers).
• High Validity (test measures intended construct).
• Representative Norms (benchmark scores from relevant population).
Classifications:
• By language: Verbal, Non-Verbal, Performance.
• By administration: Individual vs. Group tests.
• By timing: Speed tests (time pressure) vs. Power tests (ample time to assess complexity).
Applications: intelligence, aptitude, achievement, personality, attitudes, vocational interests.

Four levels of measurement: Nominal (categories), Ordinal (rank order), Interval (equal units, no true zero), Ratio (equal units, true zero).
Graphical representations:
• Bar diagram → categorical data on nominal/ordinal scales.
• Histogram → interval/ratio data; contiguous bars.
• Frequency polygon → line graph of class midpoints.
Measures of Central Tendency:
• Mean: $\bar{X} = \frac{\sum<em>{i=1}^{N} X</em>i}{N}$
• Median: value that splits ordered distribution into two equal halves.
• Mode: most frequently occurring score.
Descriptive vs. Inferential statistics: description/summarisation versus drawing general conclusions (e.g., significance tests, confidence intervals).

Lack of absolute measurement zero for many constructs.
Relative nature of psychological scales (interval level rarely attains ratio properties).
Subjectivity in qualitative data interpretation; researcher reflexivity required.

Case Study: in-depth investigation of a single unit.
Control Group vs. Experimental Group: baseline vs. IV exposure.
Dependent Variable (DV): measured outcome.
Independent Variable (IV): manipulated factor.
Hypothesis: tentative, testable prediction of relationships.
Norms: comparative standards based on large samples.
Reliability & Validity: consistency and accuracy of measurement.
Speed vs. Power Test: time-based vs. difficulty-based assessment emphasis.
Qualitative vs. Quantitative methods: narrative/interpretive vs. numerical/statistical analyses.
Survey: questionnaire/interview-based method to sample opinions or behaviours.

Understanding diverse methodologies empowers researchers to align questions with the most suitable design, enhancing scientific rigour.
Ethical safeguards not only protect participants but also uphold public trust in psychological science.
Integration of descriptive, predictive, and experimental approaches allows psychology to move from observation to intervention, influencing education, health, industry, and policy.