Certificate Course in Public Sector Research Methods

Participants can formulate focused research questions, objectives and boundaries for a public sector study.

• Problem statements separated from assumptions, symptoms and preferred solutions
• SMART research objectives aligned with defined decisions and users
• Primary and secondary research questions sequenced for logical inquiry
• Hypotheses framed where variables, relationships and evidence permit testing
• Study boundaries set by geography, population, timeframe and resources
• Conceptual definitions specified for contested policy and programme terms

Participants can develop a theory of change that identifies assumptions, outcomes and evidence requirements.

• Theory of Change links activities, outputs, outcomes and impacts
• Causal assumptions surfaced through backward mapping from intended outcomes
• External factors distinguished from controllable programme implementation conditions
• Results chains tested for plausible causal links and missing steps
• Indicators assigned to outputs, outcomes, assumptions and contextual conditions
• Contribution claims framed without overstating attribution from limited evidence

Participants can select a research design suited to the question, context and available evidence.

• Cross-sectional, longitudinal and repeated-measures designs compared for public studies
• Experimental and quasi-experimental designs assessed for causal inference
• Case study design applied to complex implementation and institutional questions
• Before-and-after comparisons examined for confounding and selection threats
• Mixed-methods designs integrated through convergent and explanatory approaches
• Design choices justified against feasibility, ethics, timing and decision needs

Participants can prepare ethical safeguards for research involving public service users and vulnerable groups.

• Informed consent procedures matched to literacy, risk and participant capacity
• Do-no-harm principles applied to sensitive policy and humanitarian research
• Safeguarding risks identified when interviewing children and vulnerable adults
• Confidentiality protocols separate identities, responses and reporting outputs
• Data minimisation applied when collecting personal and sensitive information
• Ethical review documentation records risks, mitigations and referral arrangements

Participants can develop probability sampling plans and calculate defensible sample sizes.

• Target populations, sampling frames and units of analysis defined
• Simple random sampling selected when complete population lists exist
• Systematic sampling applied using intervals, random starts and ordered lists
• Stratified sampling improves representation of priority population subgroups
• Cluster sampling planned for dispersed populations and fieldwork constraints
• Sample size calculations consider precision, confidence and design effects

Participants can select and document non-probability sampling strategies for qualitative and hard-to-reach populations.

• Purposive sampling recruits information-rich cases against defined criteria
• Maximum variation sampling captures contrasting experiences and service contexts
• Snowball sampling managed to reduce network and gatekeeper bias
• Quota sampling structures recruitment across priority demographic categories
• Theoretical sampling supports iterative qualitative inquiry and emerging themes
• Saturation decisions documented using evidence needs rather than intuition

Participants can design questionnaires that measure concepts accurately and minimise response error.

• Constructs operationalised into measurable variables and response categories
• Closed questions written with mutually exclusive and exhaustive options
• Likert scales designed with balanced anchors and consistent direction
• Recall periods specified to reduce memory error and telescoping
• Double-barrelled, leading and ambiguous questions identified and revised
• Questionnaire flow sequenced from screening through sensitive demographic items

Participants can prepare interview, focus group and observation methods for public sector research.

• Semi-structured interview guides aligned with research questions and constructs
• Probing techniques elicit examples, mechanisms, exceptions and unintended effects
• Focus group discussion guides manage participation, disagreement and confidentiality
• Key informant interviews target institutional knowledge and decision influence
• Observation protocols record behaviours, settings, interactions and service processes
• Field notes distinguish direct observations, participant accounts and researcher reflections

Participants can pilot data collection instruments and revise them using documented evidence.

• Cognitive interviewing tests respondent interpretation of survey questions
• Pilot samples test duration, sequencing, skip logic and comprehension
• Enumerator feedback identifies translation, terminology and administration problems
• Reliability checks examine consistency across items, interviewers and sessions
• Content validity assessed against constructs, indicators and expert judgement
• Revision logs document changes, reasons and approved instrument versions

Participants can create fieldwork plans that control quality, risk and documentation.

• Fieldwork plans allocate roles, routes, timelines and supervision responsibilities
• Enumerator training covers protocols, neutrality, consent and respondent protection
• Daily quality checks identify missing data, outliers and protocol deviations
• Back-checks and spot-checks verify interviews and enumerator conduct
• Response rate monitoring triggers recruitment adjustments and corrective actions
• Incident logs record safeguarding, security and data quality concerns

Participants can prepare research data for analysis using transparent cleaning and documentation procedures.

• Codebooks define variables, labels, values, formats and missingness rules
• Data entry validation controls ranges, formats and logical consistency
• Missing data patterns examined before deletion, imputation or exclusion
• Outliers investigated using source checks, distributions and contextual knowledge
• Data cleaning logs preserve original values, changes and decision rationale
• Version control separates raw, cleaned, analysis and reporting datasets

Participants can summarise quantitative data and produce clear evidence displays.

• Frequency tables summarise categorical variables and response distributions
• Mean, median and mode selected according to measurement characteristics
• Percentages calculated with correct denominators and subgroup comparisons
• Cross-tabulations reveal patterns between service users, locations and outcomes
• Bar charts, line charts and maps matched to analytical purpose
• Data visualisations labelled with sources, units, dates and caveats

Participants can interpret statistical relationships and uncertainty without making unsupported causal claims.

• Confidence intervals communicate estimate precision and plausible population ranges
• Statistical significance distinguished from practical and policy significance
• Chi-square tests assess association between categorical variables
• Correlation coefficients interpreted without assuming causation or direction
• Confounding variables considered before attributing observed group differences
• Findings qualified using sample limitations, measurement error and uncertainty

Participants can code qualitative evidence and produce defensible analytical themes.

• Transcripts prepared with identifiers removed and contextual details retained
• Open coding labels meaningful segments using consistent descriptive terms
• Codebooks define code names, inclusion criteria and exclusion criteria
• Thematic analysis groups codes into patterns, mechanisms and explanations
• Negative cases examined to challenge dominant interpretations and assumptions
• Analytic memos record decisions, emerging findings and evidence gaps

Participants can combine qualitative and quantitative findings into coherent public sector conclusions.

• Triangulation compares findings across methods, sources, groups and timeframes
• Joint displays align quantitative patterns with qualitative explanatory evidence
• Convergence, complementarity and contradiction classified across evidence strands
• Administrative records compared with survey findings for consistency and gaps
• Integrated conclusions distinguish confirmed findings from unresolved discrepancies
• Mixed-methods reporting explains how each evidence source shaped conclusions

Participants can assess programme performance using recognised evaluation criteria and evidence standards.

• OECD DAC criteria applied to relevance, coherence, effectiveness and impact
• Efficiency assessment compares resources, processes, outputs and service reach
• Sustainability analysis examines institutional, financial and community continuation factors
• Evaluation questions linked to criteria, indicators, methods and evidence sources
• Counterfactual evidence assessed for credibility, feasibility and ethical acceptability
• Evaluation matrices organise questions, indicators, sources and analytical methods

Participants can write research reports that communicate methods, findings and recommendations accurately.

• Executive summaries present decisions, key findings and recommended actions
• Methods sections document design, sampling, instruments and analytical procedures
• Findings organised around research questions rather than data collection tools
• Conclusions interpret evidence without repeating descriptive results verbatim
• Recommendations specify actions, owners, timescales and implementation conditions
• Limitations statements explain constraints without undermining valid findings

Participants can present research findings clearly to technical, managerial and political audiences.

• Audience analysis identifies decision authority, evidence needs and likely concerns
• Policy briefs structure context, evidence, options and recommended action
• Presentation storylines move from decision question to supported conclusion
• Key messages expressed using precise claims, numbers and qualifications
• Question-and-answer preparation anticipates methodological challenge and political sensitivity
• Communication products distinguish technical annexes from senior decision materials

Participants can build, review and present a complete research package for a defined public sector decision.

• Research brief defines decision context, users, questions and study scope
• Theory of Change identifies causal assumptions, indicators and evidence priorities
• Methods protocol specifies design, sampling, instruments and ethical safeguards
• Analysis plan sets quantitative tests, coding procedures and triangulation approach
• Draft report presents findings, limitations, conclusions and actionable recommendations
• Peer review tests methodological coherence, evidence traceability and presentation clarity