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Sampling Techniques and Survey Design Training Course

Online Training Download PDF
Upcoming Training Schedules 14 locations
Location Duration Next Start Date Dates Available Action
Nairobi, Kenya 10 days Jul 13, 2026 104 dates
Accra, Ghana 10 days Aug 10, 2026 31 dates
Addis Ababa, Ethiopia 10 days Jul 13, 2026 31 dates
Cape Town, South Africa 10 days Jul 20, 2026 52 dates
Dar es Salaam, Tanzania 10 days Aug 17, 2026 26 dates
Dubai, UAE 10 days Jul 20, 2026 52 dates
Istanbul, Turkey 10 days Jul 20, 2026 16 dates
Kampala, Uganda 10 days Aug 3, 2026 31 dates
Kigali, Rwanda 10 days Aug 3, 2026 52 dates
Kuala Lumpur, Malaysia 10 days Jul 13, 2026 31 dates
Mombasa, Kenya 10 days Jul 13, 2026 52 dates
Pretoria, South Africa 10 days Jul 13, 2026 52 dates
Singapore 10 days Jul 27, 2026 31 dates
Zanzibar, Tanzania 10 days Sep 7, 2026 16 dates

Sampling Techniques and Survey Design Training Course

Course Overview

The Sampling Techniques and Survey Design Training Course is a comprehensive professional development program designed to equip participants with the knowledge, methodologies, and practical competencies required to design scientifically rigorous surveys and apply appropriate sampling techniques for research, monitoring and evaluation, market studies, impact assessments, and evidence-based decision-making. In today's data-driven environment, governments, donor agencies, non-governmental organizations, humanitarian institutions, academic organizations, and private sector entities increasingly rely on reliable survey data to measure project outcomes, assess community needs, evaluate interventions, and formulate strategic policies and programs. This course provides participants with practical approaches for developing representative samples and designing effective surveys that generate valid, reliable, and actionable information.

Sampling and survey design are fundamental components of quantitative research and monitoring and evaluation systems. Appropriate sampling methodologies ensure that survey findings accurately represent target populations, while effective survey design minimizes bias, improves response quality, and enhances the credibility of research findings. Poorly designed surveys and inappropriate sampling procedures often result in unreliable conclusions, inefficient resource utilization, and ineffective decision-making processes. This course introduces participants to internationally recognized concepts and best practices in survey methodology, probability and non-probability sampling techniques, sample size determination, questionnaire design, survey administration, digital data collection systems, data quality assurance, and statistical principles that support high-quality evidence generation and organizational performance management.

The training emphasizes practical application and experiential learning through simulations, case studies, field exercises, group assignments, and hands-on activities. Participants will gain practical experience in designing surveys, determining sample sizes, constructing sampling frames, selecting respondents, developing questionnaires, implementing digital data collection tools, conducting field supervision activities, assessing data quality, and preparing datasets for analysis and reporting. The course also explores innovative survey technologies, mobile data collection applications, cloud-based information systems, and real-time monitoring technologies that improve survey efficiency, reduce costs, and strengthen evidence-based planning and decision-making processes.

Upon successful completion of this course, participants will possess the competencies necessary to design and implement scientifically sound surveys and apply appropriate sampling methodologies that generate reliable and high-quality information for monitoring and evaluation, research, policy development, and organizational learning. The knowledge and practical skills acquired through this training will enable professionals to improve evidence generation, strengthen project accountability, enhance decision-making capabilities, and contribute to sustainable development outcomes and organizational effectiveness.

Course Objectives

1.     Understand the concepts, principles, and applications of sampling techniques and survey design methodologies.

2.     Differentiate between probability and non-probability sampling approaches and their applications.

3.     Develop representative sampling frames and determine appropriate sample sizes.

4.     Design scientifically sound surveys and data collection instruments.

5.     Apply survey administration methodologies and field implementation procedures effectively.

6.     Utilize digital technologies and mobile applications in survey implementation.

7.     Establish data quality assurance and verification mechanisms.

8.     Apply ethical principles and professional standards in survey research and sampling processes.

9.     Prepare survey datasets for statistical analysis and reporting.

10.  Utilize survey findings for evidence-based decision-making, policy development, and organizational learning.

Organizational Benefits

1.     Improved quality and reliability of organizational surveys and research studies.

2.     Enhanced evidence-based planning and strategic decision-making capabilities.

3.     Strengthened monitoring, evaluation, and learning systems.

4.     Improved project performance measurement and reporting mechanisms.

5.     Enhanced efficiency in survey planning and implementation processes.

6.     Improved data quality management and information systems.

7.     Increased credibility and validity of research findings and evaluations.

8.     Strengthened organizational learning and knowledge management practices.

9.     Improved policy formulation and program design processes.

10.  Enhanced organizational accountability and sustainable development performance.

Target Participants

This course is designed for Monitoring and Evaluation Officers, Researchers, Project Managers, Program Managers, Government Officials, NGO Professionals, Humanitarian Program Managers, Research Assistants, Survey Coordinators, Data Analysts, Statisticians, Information Management Officers, Strategic Planning Officers, Development Practitioners, Donor-Funded Project Personnel, Academic Researchers, Community Development Officers, Consultants, Corporate Social Responsibility Managers, and professionals responsible for research, monitoring and evaluation, surveys, policy analysis, and evidence generation.

Course Outline

Module 1: Introduction to Sampling Techniques and Survey Design

·       Concepts and principles of survey methodology and sampling techniques

·       Importance of sampling and survey design in research and monitoring systems

·       Components and characteristics of effective survey systems

·       Relationship between sampling methodologies and evidence generation

·       Applications of survey research in development and organizational settings

·       International standards and best practices in survey methodology

Case Study: Designing a survey framework for assessing national health service delivery performance.

Module 2: Probability Sampling Techniques

·       Principles and assumptions of probability sampling methodologies

·       Simple random sampling techniques and applications

·       Systematic sampling procedures and implementation strategies

·       Stratified sampling methodologies and proportional allocation techniques

·       Cluster sampling approaches and applications

·       Multi-stage sampling techniques and operational considerations

Case Study: Applying probability sampling techniques for a national household income and expenditure survey.

Module 3: Non-Probability Sampling Techniques

·       Principles and applications of non-probability sampling methodologies

·       Convenience and purposive sampling approaches

·       Quota sampling and participant selection procedures

·       Snowball and chain referral sampling techniques

·       Theoretical and judgmental sampling applications

·       Strengths, limitations, and bias considerations in non-probability sampling

Case Study: Utilizing purposive and snowball sampling techniques for qualitative assessments of youth employment programs.

Module 4: Sample Size Determination and Sampling Frame Development

·       Principles of sample size determination methodologies

·       Statistical considerations in sample size calculations

·       Confidence intervals and margin of error concepts

·       Development and management of sampling frames

·       Management of sampling errors and non-response challenges

·       Sample allocation and respondent selection procedures

Case Study: Determining sample sizes and constructing sampling frames for an agricultural productivity survey.

Module 5: Survey Design and Questionnaire Development

·       Principles of survey design and research planning

·       Development of survey objectives and research questions

·       Questionnaire construction and measurement scale development

·       Development of open-ended and closed-ended questions

·       Questionnaire sequencing and logical flow techniques

·       Pre-testing and piloting of survey instruments

Case Study: Designing beneficiary satisfaction surveys for social protection and community development programs.

Module 6: Survey Administration and Field Management

·       Survey implementation planning and logistics management

·       Enumerator recruitment and training methodologies

·       Field supervision and coordination techniques

·       Data collection protocols and respondent engagement strategies

·       Management of operational challenges during field activities

·       Monitoring and evaluation of survey implementation processes

Case Study: Managing field data collection operations for a nationwide education assessment survey.

Module 7: Digital Technologies in Survey Implementation

·       Introduction to mobile and web-based survey technologies

·       Digital questionnaire development methodologies

·       Mobile data collection applications and platforms

·       Cloud-based information management systems

·       Real-time monitoring and supervision technologies

·       Emerging innovations in digital survey methodologies

Case Study: Implementing digital survey technologies for humanitarian needs assessments.

Module 8: Data Quality Assurance and Verification Systems

·       Principles of data quality management and assurance

·       Data validation and verification methodologies

·       Field editing and consistency assessment procedures

·       Error detection and correction techniques

·       Data auditing and quality control mechanisms

·       Strategies for improving survey data reliability and validity

Case Study: Conducting data quality assessments in donor-funded agricultural development surveys.

Module 9: Ethical Considerations in Survey Research

·       Principles of research ethics and professional conduct

·       Informed consent and respondent rights protection

·       Confidentiality and privacy management practices

·       Ethical considerations for vulnerable populations

·       Management of sensitive information and data security requirements

·       Compliance with legal and regulatory frameworks

Case Study: Applying ethical principles in household surveys involving vulnerable communities.

Module 10: Data Management and Preparation for Analysis

·       Data coding and classification methodologies

·       Database development and management procedures

·       Data cleaning and validation techniques

·       Management of missing data and inconsistencies

·       Preparation of datasets for statistical analysis

·       Documentation and metadata management practices

Case Study: Preparing survey datasets for evaluation of a public health intervention program.

Module 11: Survey Data Analysis and Reporting

·       Descriptive statistical analysis methodologies

·       Frequency distributions and cross-tabulation techniques

·       Interpretation and synthesis of survey findings

·       Data visualization and presentation approaches

·       Preparation of analytical reports and stakeholder presentations

·       Development of evidence-based recommendations

Case Study: Preparing analytical reports for monitoring and evaluation of a poverty reduction project.

Module 12: Emerging Trends and Innovations in Sampling and Survey Design

·       Big data and advanced survey methodologies

·       Artificial intelligence and machine learning applications

·       Real-time analytics and business intelligence systems

·       Geographic Information Systems and spatial sampling applications

·       Innovations in mobile and cloud-based survey technologies

·       Future trends in survey research and evidence generation

Case Study: Applying innovative survey methodologies and digital technologies in multi-country development research programs.

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.

 

 

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