Training course

Overview

Sampling and Survey Methods is a professional training course designed to build practical expertise in selecting representative samples, designing high-quality surveys, and generating reliable data for research, monitoring, evaluation, market intelligence, organisational studies, and evidence-based decision-making. The course provides a structured understanding of sampling theory, probability and non-probability sampling techniques, sample size determination, survey design, questionnaire development, fieldwork planning, data quality assurance, and survey implementation. Participants will learn how to move systematically from a research population and study objectives to an appropriate sampling strategy and defensible survey methodology.

The training provides comprehensive coverage of sampling frames, sampling units, inclusion and exclusion criteria, simple random sampling, systematic sampling, stratified sampling, cluster sampling, multistage sampling, and probability proportional to size methods. It also examines purposive, quota, convenience, snowball, and other non-probability approaches, with emphasis on understanding their appropriate applications and limitations. Participants will use practical tools such as Excel and survey platforms to develop sampling plans, calculate sample sizes, construct sampling procedures, allocate samples across population groups, and assess potential sources of sampling error, coverage error, nonresponse, and selection bias.

Survey design is addressed from both methodological and practical perspectives, covering questionnaire architecture, question wording, response scales, skip logic, routing, piloting, translation, interviewer instructions, consent procedures, digital data collection, and field supervision. Participants will work through realistic case studies and exercises involving household surveys, customer surveys, employee surveys, community assessments, programme evaluations, market research, and organisational research. Emphasis is placed on established survey research principles, ethical practice, data protection, quality control, documentation, and transparent reporting so that survey findings can be interpreted appropriately and communicated with confidence.

By the end of the course, participants will be able to design and implement sampling and survey approaches that are methodologically appropriate, operationally feasible, and aligned with research objectives and available resources. Advanced sessions address weighting, design effects, complex survey designs, nonresponse adjustment, calibration concepts, survey quality assessment, and interpretation of sampling uncertainty. Through practical exercises, case studies, sampling-plan development, questionnaire reviews, fieldwork simulations, and an applied capstone assignment, participants will develop the skills required to produce credible survey evidence and make informed methodological decisions across professional research and data-collection environments.

Course Duration

5 Days (40 Hours)

Target Participants

This course is suitable for:

• Researchers, research officers, and research assistants

• Monitoring, Evaluation, Research and Learning (MERL/MEL) professionals

• Survey coordinators, fieldwork managers, and data-collection supervisors

• Programme, project, and development professionals involved in assessments and evaluations

• Market research and customer insights professionals

• Business, policy, social science, and public-sector analysts

• Data analysts and professionals responsible for primary data collection

• Academics, lecturers, postgraduate researchers, and research consultants

• NGO, government, and international development professionals conducting surveys

• Professionals responsible for designing, reviewing, commissioning, or interpreting survey research

Course Objectives

By the end of the training, participants will be able to:

• Explain fundamental sampling and survey research concepts, terminology, principles, and methodological assumptions

• Define target populations, study populations, sampling units, sampling frames, and eligibility criteria appropriately

• Select suitable probability and non-probability sampling methods for different research objectives and operational contexts

• Calculate and justify survey sample sizes using appropriate assumptions and practical considerations

• Design stratified, cluster, multistage, and other complex sampling approaches

• Identify and manage sampling error, coverage error, nonresponse, selection bias, and other sources of survey error

• Develop clear, valid, reliable, and logically structured questionnaires for different survey populations

• Apply best practices for question wording, response options, scales, skip patterns, routing, translation, and questionnaire testing

• Plan survey fieldwork, interviewer training, supervision, quality assurance, and digital data-collection processes

• Apply ethical principles, informed consent, confidentiality, privacy, and responsible data-management practices

• Use practical tools such as Excel and digital survey platforms to develop and manage sampling and survey workflows

• Apply weighting, design-effect, nonresponse-adjustment, and complex-survey concepts at an appropriate professional level

• Evaluate survey quality and document methodological decisions transparently

• Interpret sampling uncertainty and communicate survey findings responsibly to technical and non-technical audiences

• Develop a complete sampling and survey methodology for a real-world research or evaluation assignment

Course Content

Day 1: Foundations of Sampling and Survey Research

Module 1: Sampling Principles, Research Populations, and Survey Methodology

1.      Introduction to Sampling and Survey Methods

·         Purpose and role of sampling in research and evidence generation

·         Census versus sample surveys

·         Key survey research terminology and methodological concepts

·         Applications in research, evaluation, market intelligence, and organisational studies

·         Case study: selecting a survey approach for a national programme assessment

2.      Research Objectives, Questions, and Survey Design Logic

·         Translating research objectives into measurable information requirements

·         Research questions, indicators, variables, and hypotheses

·         Choosing an appropriate survey design

·         Cross-sectional, longitudinal, repeated cross-sectional, and panel approaches

·         Exercise: developing a survey methodology from research questions

3.      Target Populations, Study Populations, and Sampling Units

·         Defining target and accessible populations

·         Sampling units and observation units

·         Inclusion and exclusion criteria

·         Geographic, organisational, household, individual, and institutional populations

·         Managing population heterogeneity and eligibility requirements

4.      Sampling Frames and Frame Quality

·         Definition and purpose of sampling frames

·         Sources of sampling frames

·         Frame completeness, accuracy, duplication, and timeliness

·         Undercoverage and overcoverage

·         Exercise: assessing the quality of a hypothetical sampling frame

5.      Probability and Non-Probability Sampling

·         Principles of probability sampling

·         Random selection and known selection probabilities

·         Overview of non-probability approaches

·         Appropriate and inappropriate applications

·         Strengths, limitations, and interpretation considerations

6.      Simple Random Sampling

·         Principles and assumptions

·         Sampling with and without replacement

·         Random number generation

·         Sample selection using Excel and digital tools

·         Practical exercise: drawing and documenting a simple random sample

7.      Systematic Sampling

·         Sampling intervals and selection procedures

·         Random starts

·         Periodicity and ordering risks

·         Applications in household, customer, employee, and administrative lists

·         Exercise: constructing a systematic sampling procedure

8.      Stratified Sampling

·         Rationale for stratification

·         Identifying appropriate strata

·         Proportionate and disproportionate allocation

·         Improving subgroup representation

·         Case study: stratifying a survey across geographic and demographic groups

9.      Cluster and Multistage Sampling Concepts

·         Cluster sampling principles

·         Primary, secondary, and final sampling units

·         Multistage sample selection

·         Operational advantages and statistical implications

·         Practical exercise: developing a two-stage household survey design

10.  Sampling Methodology Documentation and Quality Review

·         Documenting population, frame, units, method, and selection procedures

·         Sampling-plan templates

·         Quality-control checklists

·         Methodological assumptions and limitations

·         Day 1 practical assignment: prepare a preliminary sampling plan

Day 2: Sample Size, Survey Questionnaire Design, and Pilot Testing

Module 2: Sample Size Determination, Questionnaire Development, and Survey Preparation

1.      Principles of Survey Sample Size Determination

·         Relationship between population, sample size, precision, and confidence

·         Estimating proportions and means

·         Confidence levels and margins of error

·         Practical sample-size considerations

·         Exercise: calculating initial sample-size requirements

2.      Sample Size Calculations and Adjustment Factors

·         Finite population correction

·         Expected prevalence or proportion

·         Design effect

·         Anticipated nonresponse

·         Worked examples using Excel and sample-size templates

3.      Statistical Power and Precision in Survey Planning

·         Statistical power concepts

·         Minimum detectable differences

·         Subgroup analysis requirements

·         Precision versus operational cost

·         Balancing methodological and budget constraints

4.      Allocating Samples Across Strata and Population Groups

·         Proportionate allocation

·         Equal and disproportionate allocation

·         Optimal allocation concepts

·         Oversampling priority or hard-to-reach groups

·         Practical exercise: developing a stratified sample allocation

5.      Questionnaire Design Principles

·         Linking questions to research objectives and indicators

·         Questionnaire structure and sequencing

·         Introduction, eligibility, core questions, and closing sections

·         Respondent burden and survey length

·         Questionnaire design checklist

6.      Writing Clear and Unbiased Survey Questions

·         Avoiding ambiguity, double-barrelled questions, and leading wording

·         Appropriate terminology and reading levels

·         Open-ended versus closed-ended questions

·         Recall periods and reference periods

·         Exercise: identifying and correcting poorly designed questions

7.      Response Scales, Measurement, and Question Formats

·         Nominal, ordinal, interval, and continuous measures

·         Likert-type scales and rating questions

·         Frequency, agreement, satisfaction, and importance scales

·         Numeric and categorical responses

·         Managing “don't know,” “not applicable,” and refusal responses

8.      Questionnaire Routing, Skip Logic, and Survey Flow

·         Screening and eligibility questions

·         Conditional routing

·         Skip patterns and branching

·         Preventing inconsistent respondent pathways

·         Digital survey logic exercise

9.      Questionnaire Piloting and Cognitive Testing

·         Purpose and stages of pilot testing

·         Cognitive interviewing concepts

·         Testing comprehension, recall, response processes, and sensitivity

·         Recording pilot findings and revising instruments

·         Case study: redesigning a questionnaire following pilot results

10.  Survey Instruments, Documentation, and Readiness Review

·         Final questionnaire version control

·         Enumerator instructions and field protocols

·         Codebooks and variable specifications

·         Consent scripts and respondent information

·         Practical exercise: complete survey instrument readiness review

Day 3: Survey Fieldwork, Digital Data Collection, and Quality Assurance

Module 3: Survey Implementation, Field Operations, and Data Quality Management

1.      Survey Fieldwork Planning and Operational Design

·         Developing fieldwork plans and schedules

·         Geographic and organisational deployment

·         Team structures and responsibilities

·         Logistics, materials, communications, and escalation procedures

·         Case study: planning a multi-location household survey

2.      Interviewer Recruitment, Training, and Standardisation

·         Interviewer selection criteria

·         Training objectives and practical demonstrations

·         Standardised introductions and question administration

·         Role-play and mock interviews

·         Assessing interviewer readiness and competency

3.      Respondent Contact, Consent, and Ethical Survey Practice

·         Informed consent principles

·         Voluntary participation and withdrawal

·         Confidentiality and privacy

·         Handling sensitive questions and vulnerable respondents

·         Ethical fieldwork scenarios and response protocols

4.      Digital Survey Data Collection

·         Computer-assisted and mobile-assisted data collection

·         Digital questionnaire configuration

·         Mandatory fields, validation rules, and constraints

·         Offline and online collection considerations

·         Practical exercise: building a digital survey workflow

5.      Field Supervision and Interview Quality Control

·         Supervisor responsibilities

·         Daily monitoring procedures

·         Back-checks and verification

·         Spot checks and accompanied interviews

·         Managing interviewer performance and protocol deviations

6.      Survey Nonresponse and Contact Strategies

·         Unit and item nonresponse

·         Refusals, unavailable respondents, and incomplete interviews

·         Callbacks and revisits

·         Contact protocols and response-rate monitoring

·         Exercise: developing a nonresponse management plan

7.      Sampling Errors and Nonsampling Errors

·         Sampling error and sampling variability

·         Coverage and frame errors

·         Measurement and interviewer errors

·         Processing and data-entry errors

·         Survey error framework and quality assessment

8.      Data Validation and Real-Time Quality Monitoring

·         Range and consistency checks

·         Duplicate detection

·         Missing-data monitoring

·         Interview duration and paradata checks

·         Real-time field dashboards and quality indicators

9.      Survey Security, Privacy, and Data Governance

·         Secure handling of respondent information

·         Access controls and data-transfer procedures

·         Data minimisation and retention

·         Anonymisation and de-identification concepts

·         Applying organisational data-governance policies

10.  Fieldwork Simulation and Survey Quality Improvement

·         Simulated survey deployment

·         Identifying operational and methodological problems

·         Corrective-action planning

·         Supervisor feedback and quality review

·         Practical exercise: produce a fieldwork quality-improvement plan

Day 4: Advanced Sampling, Weighting, and Survey Analysis Considerations

Module 4: Complex Survey Designs, Weighting, Bias Adjustment, and Advanced Quality Assessment

1.      Advanced Stratified, Cluster, and Multistage Sampling

·         Designing complex probability samples

·         Sampling at multiple levels

·         Selection probabilities across stages

·         Practical design considerations

·         Case study: developing a national multistage survey design

2.      Probability Proportional to Size Sampling

·         PPS sampling principles

·         Size measures and selection probabilities

·         Applications in cluster and multistage designs

·         Operational considerations and implementation

·         Exercise: constructing a simplified PPS sampling procedure

3.      Design Effects and Complex Sample Efficiency

·         Why cluster and stratification affect precision

·         Intraclass correlation concepts

·         Design-effect interpretation

·         Effective sample size

·         Applying design effects during survey planning

4.      Sampling Weights and Selection Probabilities

·         Purpose of survey weights

·         Base weights and inverse probability concepts

·         Unequal selection probabilities

·         Weight construction and documentation

·         Practical exercise: calculating basic sampling weights

5.      Nonresponse Adjustment and Weighting

·         Assessing patterns of nonresponse

·         Nonresponse adjustment cells

·         Response propensity concepts

·         Weight adjustment procedures

·         Evaluating residual nonresponse bias

6.      Post-Stratification and Calibration Concepts

·         Aligning survey estimates with known population benchmarks

·         Post-stratification principles

·         Calibration concepts

·         Auxiliary information

·         Case study: improving population representation through adjustment

7.      Non-Probability Sampling and Bias Management

·         Purposive, quota, convenience, snowball, and respondent-driven approaches

·         Appropriate research applications

·         Selection mechanisms and generalisability limitations

·         Transparency in reporting

·         Exercise: evaluating alternative non-probability sampling strategies

8.      Hard-to-Reach Populations and Special Survey Designs

·         Access challenges and coverage limitations

·         Rare populations and oversampling

·         Hidden and mobile populations

·         Respondent recruitment strategies

·         Ethical and operational considerations

9.      Survey Quality Assessment and Methodological Risk

·         Response rates and completion rates

·         Coverage assessment

·         Measurement quality

·         Fieldwork and processing quality

·         Developing a survey quality dashboard

10.  Advanced Sampling Case Study and Design Review

·         Review of a complete complex sampling design

·         Identification of methodological risks

·         Weighting and precision considerations

·         Peer review of sampling documentation

·         Practical exercise: defend and improve an advanced sampling plan

Day 5: Survey Reporting, Evaluation, and Applied Sampling Project

Module 5: Survey Methodology Reporting, Evidence Quality, and Applied Capstone

1.      Survey Methodology Reporting Standards and Documentation

·         Documenting target and study populations

·         Sampling-frame description

·         Sampling method and sample-size justification

·         Fieldwork procedures and response outcomes

·         Methodology-report templates and checklists

2.      Reporting Sampling Uncertainty and Survey Limitations

·         Sampling variability

·         Confidence intervals and margins of error

·         Design effects and effective sample size

·         Nonresponse and coverage limitations

·         Communicating uncertainty without overstating precision

3.      Interpreting Survey Findings Responsibly

·         Descriptive versus inferential interpretation

·         Population estimates and subgroup comparisons

·         Statistical significance versus practical importance

·         Avoiding unsupported generalisation

·         Case study: identifying misleading survey conclusions

4.      Survey Data Quality Indicators and Performance Metrics

·         Response and completion rates

·         Item nonresponse

·         Interview duration and breakoff rates

·         Back-check and verification results

·         Quality-assurance reporting dashboards

5.      Survey Methodology Standards, Guidelines, and Best Practices

·         International survey research principles

·         Ethical research and informed-consent practices

·         Transparency and reproducibility

·         Documentation and version control

·         Applying recognised organisational and professional standards

6.      Survey Data Management and Reproducibility

·         Data dictionaries and codebooks

·         Questionnaire-to-dataset mapping

·         Sampling documentation and audit trails

·         File naming and version control

·         Reproducible survey workflows

7.      Survey Findings for Management, Policy, and Programme Decisions

·         Translating survey results into actionable evidence

·         Executive summaries and technical reports

·         Tables, charts, and methodological notes

·         Communicating limitations to decision-makers

·         Real-world scenario: presenting survey findings to senior stakeholders

8.      Comprehensive Sampling and Survey Case Study

·         Defining a research population and survey objectives

·         Selecting the sampling design

·         Calculating and allocating the sample

·         Developing questionnaire and fieldwork procedures

·         Peer review of the complete survey methodology

9.      Applied Survey Design and Implementation Exercise

·         Prepare a complete sampling plan

·         Develop a structured questionnaire

·         Define fieldwork and quality-control procedures

·         Identify potential sources of bias and mitigation measures

·         Present and defend methodological decisions

10.  Capstone Assessment, Lessons Learned, and Professional Action Plan

·         Presentation of the completed sampling and survey methodology

·         Technical review and facilitator feedback

·         Identification of methodological strengths and risks

·         Development of an implementation action plan

·         Final reflection on applying sampling and survey methods in professional practice