PSYCHOLOGY RESEARCH METHODS
& STATISTICS
ULTIMATE UNIVERSITY EXAM REVISION PACK
A concise, exam-focused guide to research design, ethics, measurement, descriptive
statistics, inferential statistics, and statistical test selection.
Includes: Topic summaries • Key definitions • Decision guides • Worked examples •
Exam traps • Practice questions • Answer key • Last-minute cram sheets
Original study resource • Designed for revision and exam preparation
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 1
,How to Use This Revision Pack
This resource is designed to help you move from understanding a concept to applying it in an exam. Use the full
notes for learning, the decision guides for quick recall, and the practice questions to test whether you can apply the
material without looking at the answers.
Recommended revision cycle
• 1. Read one topic and write a one-sentence explanation from memory.
• 2. Complete the relevant practice questions without using the notes.
• 3. Mark your answers and identify the exact concept behind each mistake.
• 4. Revisit weak areas using the cram sheets.
• 5. Repeat the questions later under timed conditions.
Important: Course content and the statistical tests taught on your degree may differ. Always use your module
handbook and lecturer guidance as the final authority for assessment requirements.
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 2
, PART 1 — RESEARCH METHODS
1. Research Questions, Hypotheses and Variables
Research question: the specific question a study aims to answer. A good research question is focused,
measurable, and appropriate to the design.
Hypothesis: a testable prediction about a relationship or difference. A directional hypothesis predicts the direction;
a non-directional hypothesis predicts a difference or relationship without specifying direction.
Null hypothesis (H■): generally states that there is no population effect, difference, or association. Statistical
testing evaluates whether the observed data provide sufficient evidence against H■.
Independent variable (IV): the variable manipulated or used to define groups in an experiment. Dependent
variable (DV): the outcome measured.
Confounding variable: an unwanted variable that varies systematically with the IV and can offer an alternative
explanation for the results.
Extraneous variable: any additional variable that may influence the DV. If it is controlled successfully, it is less
likely to threaten internal validity.
Operationalisation: defining exactly how an abstract construct will be measured or manipulated. For example,
“stress” might be operationalised as a score on a validated questionnaire or a physiological measure.
Exam trap: correlation does not establish causation. A relationship between two variables can arise because of
reverse causality, a third variable, or chance.
2. Research Designs
Design Core idea Strength Limitation
Experimental Researcher manipulates an IV and measures
Best design
a DVfor testing causal explanations
May be artificial; ethical/practical limits
Correlational Measures association between variables
Useful when manipulation is impossibleCannot
or inappropriate
by itself establish causation
Cross-sectional Data collected at one point in time Fast snapshot of a population Cannot show individual change over time
Longitudinal Same participants followed over time Can examine change and temporal order
Attrition, cost, and time
Case study Detailed investigation of one case or small
Rich,number
in-depth
ofinformation
cases Limited generalisability
Qualitative Explores experiences, meanings, and perspectives
Depth and contextual understanding Analysis can be time-intensive
3. Experimental Designs
Independent-groups design: different participants take part in each condition. Advantage: no order effects.
Disadvantage: participant differences can add variability.
Repeated-measures design: the same participants complete every condition. Advantage: controls for stable
individual differences. Disadvantage: order, practice, fatigue, and carryover effects.
Matched-pairs design: participants are paired on important characteristics, with each member of a pair assigned to
a different condition. It can reduce individual-difference effects but requires effective matching.
Counterbalancing: varying the order in which conditions are completed to reduce systematic order effects in
repeated-measures designs.
4. Sampling
Method Description Key point
Simple random Every eligible population member has an equal chance of selection
Strong representativeness in principle
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 3
& STATISTICS
ULTIMATE UNIVERSITY EXAM REVISION PACK
A concise, exam-focused guide to research design, ethics, measurement, descriptive
statistics, inferential statistics, and statistical test selection.
Includes: Topic summaries • Key definitions • Decision guides • Worked examples •
Exam traps • Practice questions • Answer key • Last-minute cram sheets
Original study resource • Designed for revision and exam preparation
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 1
,How to Use This Revision Pack
This resource is designed to help you move from understanding a concept to applying it in an exam. Use the full
notes for learning, the decision guides for quick recall, and the practice questions to test whether you can apply the
material without looking at the answers.
Recommended revision cycle
• 1. Read one topic and write a one-sentence explanation from memory.
• 2. Complete the relevant practice questions without using the notes.
• 3. Mark your answers and identify the exact concept behind each mistake.
• 4. Revisit weak areas using the cram sheets.
• 5. Repeat the questions later under timed conditions.
Important: Course content and the statistical tests taught on your degree may differ. Always use your module
handbook and lecturer guidance as the final authority for assessment requirements.
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 2
, PART 1 — RESEARCH METHODS
1. Research Questions, Hypotheses and Variables
Research question: the specific question a study aims to answer. A good research question is focused,
measurable, and appropriate to the design.
Hypothesis: a testable prediction about a relationship or difference. A directional hypothesis predicts the direction;
a non-directional hypothesis predicts a difference or relationship without specifying direction.
Null hypothesis (H■): generally states that there is no population effect, difference, or association. Statistical
testing evaluates whether the observed data provide sufficient evidence against H■.
Independent variable (IV): the variable manipulated or used to define groups in an experiment. Dependent
variable (DV): the outcome measured.
Confounding variable: an unwanted variable that varies systematically with the IV and can offer an alternative
explanation for the results.
Extraneous variable: any additional variable that may influence the DV. If it is controlled successfully, it is less
likely to threaten internal validity.
Operationalisation: defining exactly how an abstract construct will be measured or manipulated. For example,
“stress” might be operationalised as a score on a validated questionnaire or a physiological measure.
Exam trap: correlation does not establish causation. A relationship between two variables can arise because of
reverse causality, a third variable, or chance.
2. Research Designs
Design Core idea Strength Limitation
Experimental Researcher manipulates an IV and measures
Best design
a DVfor testing causal explanations
May be artificial; ethical/practical limits
Correlational Measures association between variables
Useful when manipulation is impossibleCannot
or inappropriate
by itself establish causation
Cross-sectional Data collected at one point in time Fast snapshot of a population Cannot show individual change over time
Longitudinal Same participants followed over time Can examine change and temporal order
Attrition, cost, and time
Case study Detailed investigation of one case or small
Rich,number
in-depth
ofinformation
cases Limited generalisability
Qualitative Explores experiences, meanings, and perspectives
Depth and contextual understanding Analysis can be time-intensive
3. Experimental Designs
Independent-groups design: different participants take part in each condition. Advantage: no order effects.
Disadvantage: participant differences can add variability.
Repeated-measures design: the same participants complete every condition. Advantage: controls for stable
individual differences. Disadvantage: order, practice, fatigue, and carryover effects.
Matched-pairs design: participants are paired on important characteristics, with each member of a pair assigned to
a different condition. It can reduce individual-difference effects but requires effective matching.
Counterbalancing: varying the order in which conditions are completed to reduce systematic order effects in
repeated-measures designs.
4. Sampling
Method Description Key point
Simple random Every eligible population member has an equal chance of selection
Strong representativeness in principle
Psychology Research Methods & Statistics — Ultimate University Exam Revision Pack Page 3
