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Methodology

Every step of scientific research — from designing a study and collecting data to analysis, ethics and writing — explained pedagogically, step by step, each topic on its own page.

The Research Process

  1. 01What Is Scientific Research?Systematic, empirical, replicable inquiry
  2. 02The Research ProcessFrom problem to dissemination
  3. 03The Research ProblemWhat makes a researchable problem
  4. 04Research QuestionsFocused, answerable questions
  5. 05Aims and ObjectivesThe overall aim and concrete objectives
  6. 06The Literature ReviewMapping what is known and finding the gap
  7. 07Theoretical FrameworkAnchoring a study in theory
  8. 08Conceptual FrameworkA map of concepts and expected relationships
  9. 09Types of HypothesesNull/alternative, directional, research/statistical
  10. 10Variables in ResearchDependent, independent, mediator, moderator, control
  11. 11Conceptualization and OperationalizationFrom abstract concept to measurable indicator
  12. 12Unit of AnalysisWho or what is being studied
  13. 13The Research ProposalPlanning and justifying the study
  14. 14Deductive, Inductive and Abductive ReasoningThree modes of reasoning in research

Research Approaches

  1. 01Quantitative ResearchMeasuring, testing and generalizing with numbers
  2. 02Qualitative ResearchMeaning, context and depth
  3. 03Mixed Methods ResearchCombining quantitative and qualitative
  4. 04Research Paradigms in PracticeOntology, epistemology and method
  5. 05Basic vs Applied ResearchKnowledge for its own sake vs solving problems
  6. 06Exploratory, Descriptive and Explanatory ResearchThe three purposes of research
  7. 07Cross-sectional vs Longitudinal ResearchA snapshot vs following over time

Research Designs

  1. 01What Is a Research Design?The blueprint linking question to evidence
  2. 02Experimental DesignManipulation, control, randomization
  3. 03Randomized Controlled TrialsThe gold standard for causal evidence
  4. 04Quasi-experimental DesignCausal inference without randomization
  5. 05Pre-experimental DesignsWeakly controlled, exploratory designs
  6. 06Between-subjects vs Within-subjectsDifferent people vs the same people
  7. 07Factorial DesignsTwo+ independent variables and interactions
  8. 08Repeated-measures and Crossover DesignsFollowing the same subjects across conditions
  9. 09Randomized Block and Latin Square DesignsControlling nuisance variation by blocking
  10. 10Correlational ResearchMeasuring association without manipulation
  11. 11Survey ResearchSystematically gathering data from a sample
  12. 12Case Study ResearchIn-depth study of a case in its context
  13. 13Cohort StudiesFollowing groups forward over time
  14. 14Case-control StudiesLooking back from outcome to exposure
  15. 15EthnographyProlonged immersion in a culture
  16. 16Grounded TheoryBuilding theory from the data
  17. 17PhenomenologyUnderstanding the essence of lived experience
  18. 18Narrative ResearchStudying the stories people tell
  19. 19Action ResearchImproving practice through cycles of action
  20. 20Design Science ResearchBuilding and evaluating artifacts
  21. 21Systematic ReviewA protocol-driven, replicable synthesis
  22. 22Meta-analysis as a MethodPooling effects across studies
  23. 23The Delphi MethodExpert consensus through anonymous rounds

Data Collection

  1. 01Primary vs Secondary DataNewly collected vs existing data
  2. 02Data Collection Methods: An OverviewMatching method to question and design
  3. 03Questionnaires and SurveysA standardized self-report instrument
  4. 04InterviewsStructured, semi-structured and unstructured
  5. 05Focus GroupsGenerating data through group interaction
  6. 06Observation MethodsWatching behaviour in its setting
  7. 07Experiments as Data CollectionGenerating data by controlled manipulation
  8. 08Document and Archival AnalysisUsing existing texts and records as data
  9. 09Pilot Studies and PretestingTesting instruments before the main study
  10. 10Secondary and Big DataAdministrative records, open data, digital traces

Measurement & Scaling

  1. 01Measurement in ResearchAssigning numbers or labels by rule
  2. 02Likert ScalesSummated rating statements
  3. 03Semantic Differential and Rating ScalesBipolar adjectives and other ratings
  4. 04Guttman and Thurstone ScalesCumulative and equal-interval scaling
  5. 05Index and Scale ConstructionCombining indicators into a composite measure
  6. 06Validity of MeasurementContent, criterion and construct validity
  7. 07Reliability of MeasurementConsistency and repeatability
  8. 08Questionnaire Design PrinciplesRules for writing good questions
  9. 09The Scale Development ProcessFrom construct definition to validation

Qualitative Analysis

  1. 01Qualitative Data Analysis: An OverviewMaking sense of non-numerical data
  2. 02Coding in Qualitative ResearchLabelling data with meaningful tags
  3. 03Thematic AnalysisIdentifying patterns as themes
  4. 04Content AnalysisSystematically categorizing text
  5. 05Grounded Theory AnalysisBuilding theory by constant comparison
  6. 06Discourse AnalysisStudying language in use and power
  7. 07Narrative AnalysisAnalysing the structure and meaning of stories
  8. 08Framework AnalysisMatrix-based systematic qualitative analysis
  9. 09TriangulationStrengthening findings with multiple sources
  10. 10Trustworthiness in Qualitative ResearchCriteria for rigour
  11. 11Reflexivity and PositionalityMaking the researcher's influence visible
  12. 12Saturation in Qualitative ResearchWhen new data add nothing new

Validity & Bias

  1. 01Internal ValidityThe soundness of a causal claim
  2. 02External Validity and GeneralizabilityExtending results beyond the study
  3. 03Construct Validity in ResearchStudying the construct you intend to
  4. 04Statistical Conclusion ValidityCorrect inference about covariation
  5. 05Threats to Internal ValidityFactors that confound causal claims
  6. 06Confounding VariablesThird variables that create spurious links
  7. 07Selection and Sampling BiasWhen the sample misrepresents the population
  8. 08Measurement and Response BiasSystematic distortion of the data
  9. 09Publication BiasThe over-representation of positive results
  10. 10Cognitive Biases in ResearchTendencies that distort the researcher's judgment
  11. 11Controlling Bias: Blinding and RandomizationDesigning bias out of a study

Research Ethics

  1. 01Principles of Research EthicsRespect, beneficence, justice
  2. 02Informed ConsentVoluntary, informed, competent participation
  3. 03Confidentiality and AnonymityProtecting identity and data
  4. 04Ethics Review Boards (IRB)Independent ethical approval
  5. 05Research MisconductFabrication, falsification, plagiarism
  6. 06Plagiarism and Academic IntegrityUsing others' work properly
  7. 07Conflict of InterestInterests that may bias judgment
  8. 08Authorship and Publication EthicsCrediting contributions fairly and honestly
  9. 09Data Management and FAIR PrinciplesMaking data findable and reusable
  10. 10Ethics with Human and Animal SubjectsThe Declaration of Helsinki and the 3Rs
  11. 11Questionable Research Practicesp-hacking, HARKing, selective reporting
  12. 12Privacy and Data Protection in ResearchSafeguarding personal and sensitive data

Scientific Writing & Communication

  1. 01Structure of a Research Paper (IMRaD)Introduction, Methods, Results, Discussion
  2. 02Writing the AbstractThe study's concise showcase
  3. 03Writing the IntroductionFrom context to gap to aim
  4. 04Writing the Methods SectionEnough detail to reproduce the study
  5. 05Reporting ResultsPresenting findings clearly, without interpretation
  6. 06Writing the Discussion and ConclusionInterpreting findings and owning limitations
  7. 07Writing a Literature ReviewSynthesis, not summary
  8. 08Citation and Referencing StylesAPA, MLA, Chicago, IEEE, Vancouver
  9. 09Avoiding Plagiarism in WritingQuoting, paraphrasing and citing well
  10. 10The Peer Review ProcessExpert scrutiny before publication
  11. 11Choosing a Journal and Impact MetricsScope fit and impact indicators
  12. 12Predatory JournalsRecognizing fake scholarly publishing
  13. 13Open Access and PreprintsMaking research freely available
  14. 14Reporting GuidelinesCONSORT, PRISMA, STROBE, COREQ
  15. 15Presenting ResearchConference talks, posters, slides
  16. 16Reproducibility and Open Science PracticesData/code sharing, preregistration, registered reports

Evidence-Synthesis Literacy

  1. 01Effect Sizes in Meta-AnalysisPutting studies on a common scale
  2. 02Fixed-effect vs Random-effects ModelsTwo assumptions for pooling
  3. 03Heterogeneity and I-squaredHow inconsistent the studies are
  4. 04Reading Forest PlotsThe visual summary of a meta-analysis
  5. 05Funnel Plots and Publication BiasDetecting missing studies graphically
  6. 06Subgroup and Sensitivity Analysis in ReviewsExploring heterogeneity and testing robustness

Causal-Inference Literacy

  1. 01Confounders, Colliders, and MediatorsWhich variables to adjust for
  2. 02Directed Acyclic Graphs (DAGs)Drawing causal assumptions explicitly
  3. 03The Potential Outcomes FrameworkCausal effect as a counterfactual
  4. 04Randomized vs Observational EvidenceWhy randomization identifies causes
  5. 05Causal Identification StrategiesRecovering causes from observational data

Scholarship Skills

  1. 01Literature Search StrategiesSearching databases systematically
  2. 02Reference Management ToolsOrganizing citations and PDFs
  3. 03Grey Literature and Searching Beyond DatabasesUnpublished and hard-to-find sources
  4. 04How to Read a Scientific PaperAn efficient, critical reading strategy
  5. 05Critical Appraisal of ResearchJudging whether a study is trustworthy
  6. 06Building a Synthesis MatrixTurning reading into a literature review

Frameworks & Standards

  1. 01CRISP-DMThe standard process for data mining
  2. 02The KDD ProcessKnowledge discovery in databases
  3. 03SEMMASAS data-mining process
  4. 04The OSEMN Data Science ProcessThe five steps of a data-science workflow
  5. 05The Team Data Science Process (TDSP)An agile, enterprise data-science lifecycle
  6. 06PICO and Question FrameworksStructuring an answerable research question
  7. 07The Research OnionPlanning methodology layer by layer
  8. 08Levels of EvidenceThe evidence hierarchy and pyramid
  9. 09The GRADE ApproachRating the certainty of evidence
  10. 10The Bradford Hill CriteriaFrom association to causation
  11. 11Risk of Bias AssessmentCritically appraising study quality
  12. 12The Research Data LifecycleFrom planning data to reusing it
  13. 13The DIKW PyramidData, information, knowledge, wisdom
  14. 14Logic Models and Theory of ChangeMapping programs from inputs to impact
  15. 15SWOT and PESTLE AnalysisFrameworks for strategic situation analysis
  16. 16Gantt Charts and Research Project ManagementPlanning and tracking a research project