This post is part of the continuing mini-series on RQ–RH–D–M across fields. Its purpose is to provide a compact, practical toolkit showing how research questions, research hypotheses or working propositions, data, and methodology can be aligned in one specific discipline.
Archaeology is especially suitable for this exercise because it naturally combines material evidence, chronology, landscape, ritual, settlement, technology, symbolic interpretation and human behavior across time. It also supports quantitative, qualitative and mixed methods designs. In this section, archaeoastronomy is explicitly included, especially in questions about the orientation of sacred structures and the interpretation of celestial alignments.
In archaeology, research design is often informed by frameworks drawn from culture history, processual archaeology, post-processual archaeology, landscape archaeology, behavioral archaeology, agency theory, ritual theory, social identity approaches and, where relevant, archaeoastronomical models of orientation, celestial alignment and sacred landscape interpretation. These frameworks guide the construction of questions and hypotheses about settlement, ritual, inequality, mobility, symbolism or spatial organization and they lead to variables derived from artifact counts, spatial distributions, architectural measures orientation data, bioarchaeological indicators, field observations, documentary interpretation or combinations of quantitative and qualitative evidence.
Note: The entries in the Methodology are intentionally general and indicative. They are meant to illustrate plausible methodological directions, not to exhaust the full range of possible methods, model variants or analytic choices available to the researcher. Researchers are not expected to apply all of the methodological tools listed in column Methodology in a single study. The entries are intended to indicate suitable methodological options or families of approaches from which the researcher selects those that best fit the research question, hypothesis, data, and design.
Archaeology – quantitative research
Descriptive questions
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RQ: What is the average grave-goods count per burial in an Early Bronze Age cemetery?
RH: The average grave-goods count per burial exceeds 3 items.
D: Grave-goods count (count); burial ID; cemetery sector (categorical); period (categorical: Early Bronze Age).
M: Descriptive statistics, one-sample tests, Poisson/negative binomial summaries, confidence intervals.
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RQ: What is the average wall thickness of domestic pottery in a Late Iron Age settlement?
RH: The average wall thickness of domestic pottery is below 7 mm.
D: Pottery wall thickness (continuous); vessel type (categorical); context ID; period (categorical: Late Iron Age).
M: Descriptive statistics, one-sample t-test or Wilcoxon signed-rank test, confidence intervals, distribution plots.
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RQ: What proportion of excavated sacred structures in a regional sample have east-facing entrances?
RH: More than half of the sacred structures have east-facing entrances.
D: Entrance orientation category (categorical/binary after coding east-facing); structure ID; site ID; ritual structure type.
M: Frequencies, proportions, binomial test, confidence intervals, circular categorization summaries.
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RQ: What is the mean azimuth orientation of medieval churches in a selected landscape?
RH: The mean church orientation clusters around the solar rising arc rather than being uniformly distributed.
D: Azimuth orientation (circular/angular); church ID; site coordinates; local horizon notes.
M: Circular mean, circular variance, Rayleigh test, rose diagrams, von Mises modeling.
Comparative questions
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RQ: Do elite and non-elite burials differ in grave-goods diversity?
RH: Elite burials have higher grave-goods diversity than non-elite burials.
D: Grave-goods diversity index (continuous/count); burial status (categorical: elite/non-elite); burial ID.
M: Independent-samples t-test, Mann–Whitney U test, OLS/count regression.
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RQ: Do hilltop and valley settlements differ in average storage capacity?
RH: Hilltop settlements have lower average storage capacity than valley settlements.
D: Storage capacity estimate (continuous); settlement type (categorical: hilltop/valley); site ID; phase.
M: t-test, ANOVA, OLS regression, multilevel modeling if features nested within sites.
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RQ: Do temples from two cultural phases differ in orientation concentration?
RH: Temples from the later phase show stronger clustering toward solar targets than temples from the earlier phase.
D: Structure azimuths (circular); phase (categorical: earlier/later); site ID; horizon corrections.
M: Watson–Williams test, Kuiper test, circular density comparison, Monte Carlo comparison of target clustering.
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RQ: Are coastal and inland ritual sites different in visibility range from their central monuments?
RH: Coastal ritual sites have greater visibility range than inland ritual sites.
D: Viewshed area (continuous); site type (categorical: coastal/inland); monument ID; DEM-derived visibility.
M: t-test, ANOVA, GIS viewshed analysis, OLS regression.
Relational / correlational questions
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RQ: Is house size associated with artifact density in a prehistoric settlement?
RH: Larger houses are associated with higher artifact density.
D: House size (continuous); artifact density (continuous); house ID; phase controls.
M: Pearson/Spearman correlation, OLS regression, multilevel regression.
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RQ: Is distance to water associated with settlement size in a Bronze Age landscape?
RH: Greater distance to water is associated with smaller settlement size.
D: Distance to water (continuous); settlement size (continuous); site ID; region.
M: Correlation, OLS regression, spatial regression, GIS distance analysis.
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RQ: Is monument azimuth associated with the declination of solar or lunar targets in sacred landscapes?
RH: Monument azimuths are significantly associated with plausible solar or lunar target declinations rather than random orientation.
D: Azimuth (circular); horizon altitude (continuous); derived declination (continuous/circular); monument ID.
M: Circular-linear association, declination modeling, Monte Carlo simulation, astronomical target matching.
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RQ: Is ceramic standardization associated with workshop centralization?
RH: Greater ceramic standardization is associated with higher workshop centralization.
D: Standardization index (continuous); workshop centralization measure (continuous/ordinal); assemblage ID.
M: Correlation, OLS regression, SEM/path modeling as alternative.
Causal / experimental-style questions
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RQ: What is the effect of a residue-cleaning treatment on the detection rate of organic traces in pottery sherds?
RH: Sherds receiving the residue-cleaning treatment show higher organic trace detection than untreated sherds.
D: Treatment condition (binary); detection outcome (binary); sherd ID; vessel type.
M: Experimental design, logistic regression, chi-square test, mixed-effects logistic model.
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RQ: Does structured training improve inter-rater agreement in lithic typology classification?
RH: Analysts receiving structured training achieve higher inter-rater agreement than analysts without training.
D: Training condition (binary); agreement statistic (continuous/categorical); analyst ID; artifact set ID.
M: Experimental/quasi-experimental design, ANCOVA, mixed-effects model, agreement analysis.
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RQ: What is the effect of reconstruction height on the measured horizon visibility of a ritual platform?
RH: Increased reconstruction height produces significantly wider horizon visibility than the baseline reconstruction.
D: Reconstruction condition (categorical); visibility arc (continuous/circular range); model ID; site ID.
M: Simulation experiment, repeated-measures ANOVA or LMM, GIS viewshed modeling.
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RQ: Does including horizon correction change whether sacred structures appear aligned to equinox sunrise?
RH: Horizon correction significantly changes the classification of equinox-aligned structures.
D: Alignment classification before/after correction (binary); azimuth; horizon altitude; structure ID.
M: Paired classification analysis, McNemar test, circular recalculation, Monte Carlo sensitivity analysis.
Archaeology – qualitative research
Ritual, symbolism, and sacred space
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RQ: How do archaeologists interpret the symbolic meaning of entrance orientation in sacred structures?
RH: Archaeologists are likely to interpret entrance orientation through ritual movement, cosmology, and controlled access to sacred space.
D: Expert interviews, excavation reports, interpretive notes, architectural descriptions.
M: Thematic analysis, discourse analysis, interpretive case study.
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RQ: How do excavators describe the relationship between monument placement and ritual experience?
RH: Excavators are likely to describe placement as linked to visibility, processional movement, and symbolic dominance.
D: Interviews, field diaries, site plans, trench notes.
M: Thematic analysis, narrative inquiry, case study.
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RQ: How do researchers interpret repeated deposition in ritual pits?
RH: Researchers are likely to interpret repeated deposition as structured ritual practice rather than accidental accumulation.
D: Interviews, field notes, deposition records, contextual descriptions.
M: Thematic analysis, qualitative content analysis, interpretive process tracing.
Archaeoastronomy and meaning
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RQ: How do archaeoastronomers interpret the cultural meaning of eastward orientation in sacred buildings?
RH: Archaeoastronomers are likely to interpret eastward orientation through solar symbolism, calendrical marking, and ritual renewal.
D: Specialist interviews, site reports, orientation datasets used interpretively, textual reflections.
M: Thematic analysis, discourse analysis, interpretive case study.
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RQ: How do researchers describe the limits of inferring astronomical intention from architectural alignment alone?
RH: Researchers are likely to emphasize context, comparison, and caution against single-cause explanations.
D: Interviews, methodological essays, site commentaries, field reflections.
M: Thematic analysis, qualitative methodology analysis, discourse analysis.
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RQ: How do local knowledge holders interpret sacred landscape alignments in relation to celestial events?
RH: Local knowledge holders are likely to connect alignments with ritual calendars, oral memory, and place-based symbolism.
D: Interviews, oral histories, landscape narratives, community reflections.
M: Thematic analysis, narrative inquiry, ethnographic case study.
Field practice and interpretation
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RQ: How do field archaeologists describe uncertainty when assigning function to ambiguous structures?
RH: Field archaeologists are likely to describe uncertainty through incomplete context, disturbed stratigraphy, and competing analogies.
D: Interviews, trench diaries, context sheets, interpretation memos.
M: Thematic analysis, phenomenological analysis, case study.
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RQ: How do specialists describe the role of context in interpreting isolated artifacts?
RH: Specialists are likely to treat context as central to meaning and chronology.
D: Interviews, catalog notes, interpretive reports, lab reflections.
M: Thematic analysis, qualitative content analysis, expert case comparison.
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RQ: How do excavation teams interpret disagreement over feature classification?
RH: Teams are likely to interpret disagreement through training differences, evidential thresholds, and disciplinary habit.
D: Team interviews, meeting notes, field logs, coding disagreements.
M: Thematic analysis, team case study, discourse analysis.
Heritage, community, and archaeological meaning
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RQ: How do local communities describe the significance of nearby archaeological sites?
RH: Communities are likely to describe significance through identity, ancestry, memory, and local pride.
D: Interviews, community meetings, local narratives, heritage notes.
M: Thematic analysis, community case study, narrative inquiry.
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RQ: How do visitors interpret authenticity in reconstructed archaeological sites?
RH: Visitors are likely to interpret authenticity through material feel, storytelling, and perceived historical accuracy.
D: Visitor interviews, field notes, interpretive materials, comment logs.
M: Thematic analysis, phenomenological analysis, visitor studies case analysis.
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RQ: How do heritage professionals describe tensions between conservation and public accessibility?
RH: Heritage professionals are likely to describe tension through preservation risk, educational value, and resource constraints.
D: Interviews, management plans, policy notes, reflective accounts.
M: Thematic analysis, policy case study, framework analysis.
Technology, documentation, and evidence
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RQ: How do archaeologists describe the interpretive value of 3D models in excavation analysis?
RH: Archaeologists are likely to describe 3D models as useful for visualization, revisiting context, and communication, but not as substitutes for excavation judgment.
D: Interviews, digital workflow notes, model-use reflections, project documentation.
M: Thematic analysis, practitioner inquiry, case study.
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RQ: How do researchers describe the strengths and limitations of GIS in landscape archaeology?
RH: Researchers are likely to describe GIS as powerful for patterning and spatial testing, but limited without contextual interpretation.
D: Interviews, project reports, GIS workflow notes, interpretive memos.
M: Thematic analysis, discourse analysis, methodological case study.
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RQ: How do archaeological teams interpret disagreements between laboratory and field evidence?
RH: Teams are likely to describe disagreement as productive but difficult, requiring negotiation across evidence types.
D: Interviews, lab reports, field notes, team meeting records.
M: Thematic analysis, team-based case study, narrative inquiry.
Archaeology – mixed methods
Archaeoastronomy, orientation, and meaning
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RQ: How are the orientations of sacred structures distributed relative to solar targets, and how do researchers interpret the ritual meaning of those alignments?
RH: Sacred structures will show non-random orientation toward solar targets; researchers are likely to interpret those patterns through ritual timing, cosmology, and symbolic eastwardness.
D: Quantitative: azimuths, horizon altitude, declination estimates, structure type; Qualitative: interviews, interpretive reports, site narratives.
M: Explanatory sequential design, circular statistics plus thematic analysis, joint display integration.
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RQ: What differences exist between structures classified as astronomically aligned and non-aligned, and how do archaeologists explain those differences in context?
RH: Astronomically aligned structures will show stronger directional clustering than non-aligned structures; archaeologists are likely to explain differences through ritual function, chronology, and local topography.
D: Quantitative: alignment classification, azimuth clustering metrics, site variables; Qualitative: expert interviews, context descriptions, field interpretations.
M: Convergent mixed methods design, circular comparison tests plus thematic/case analysis, integrated interpretation.
Settlement, landscape, and spatial use
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RQ: How is proximity to water associated with settlement size, and how do archaeologists interpret the social meaning of water access in settlement planning?
RH: Closer proximity to water will be associated with larger settlement size; archaeologists are likely to interpret water access through subsistence, mobility, and symbolic control.
D: Quantitative: distance to water, settlement size, topographic variables; Qualitative: interviews, landscape interpretations, site reports.
M: Explanatory sequential design, regression/GIS analysis plus thematic analysis, integrated interpretation.
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RQ: How do visibility measures of monuments relate to site hierarchy, and how do researchers explain the experiential meaning of visibility in ritual landscapes?
RH: Greater monument visibility will be associated with higher site hierarchy; researchers are likely to interpret visibility through procession, authority, and symbolic presence.
D: Quantitative: viewshed metrics, hierarchy indicators, monument type; Qualitative: interviews, field narratives, interpretive notes.
M: Convergent mixed methods design, GIS visibility analysis plus thematic analysis, joint display integration.
Material culture, inequality, and social interpr
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RQ: How is grave-goods richness associated with burial differentiation, and how do archaeologists interpret the social meaning of that differentiation?
RH: Greater grave-goods richness will be associated with stronger burial differentiation; archaeologists are likely to interpret differentiation through status, kinship, and ritual display.
D: Quantitative: grave-goods count/diversity, burial type, age/sex category where available; Qualitative: interpretive reports, interviews, cemetery narratives.
M: Explanatory sequential design, regression/count models plus thematic analysis, matrix-based integration.
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RQ: What differences exist in ceramic standardization across workshop zones, and how do specialists explain those differences in production organization?
RH: Workshop zones with greater centralization will show stronger ceramic standardization; specialists are likely to explain those differences through craft control, training, and exchange networks.
D: Quantitative: standardization index, workshop zone, vessel measurements; Qualitative: specialist interviews, production narratives, site documentation.
M: Convergent mixed methods design, ANOVA/regression plus thematic analysis, integrated interpretation using joint displays.
Director of Wellington based My Statistical Consultant Ltd company. Retired Associate Professor in Statistics.
Has a PhD in Statistics and over 45 years experience as a university professor, consultant, international researcher and government advisor.