Subscribe for Course Updates

Be the first to know when new training courses are scheduled or dates are updated.

Verification code Click image to refresh

You can unsubscribe at any time • training@fdc-k.org

Chat with our consultants

Descriptive Statistics for Monitoring and Evaluation 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 3, 2026 31 dates
Addis Ababa, Ethiopia 10 days Jul 13, 2026 31 dates
Cape Town, South Africa 10 days Jul 27, 2026 52 dates
Dar es Salaam, Tanzania 10 days Aug 10, 2026 26 dates
Dubai, UAE 10 days Jul 27, 2026 52 dates
Istanbul, Turkey 10 days Aug 17, 2026 16 dates
Kampala, Uganda 10 days Aug 10, 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 27, 2026 52 dates
Singapore 10 days Jul 13, 2026 31 dates
Zanzibar, Tanzania 10 days Jul 27, 2026 16 dates

Descriptive Statistics for Monitoring and Evaluation Training Course

Course Overview

The Descriptive Statistics for Monitoring and Evaluation Training Course is a comprehensive professional development program designed to equip participants with practical knowledge and analytical skills required to organize, summarize, interpret, and communicate data generated through monitoring and evaluation systems. In today's evidence-driven environment, organizations across government institutions, non-governmental organizations, humanitarian agencies, donor-funded projects, healthcare systems, and development programs increasingly rely on statistical information to measure performance, assess progress, demonstrate accountability, and support strategic decision-making. Descriptive statistics serve as the foundation of data analysis by transforming complex datasets into meaningful information that can be understood and utilized effectively by decision-makers and stakeholders.

Monitoring and evaluation systems generate large volumes of quantitative and qualitative data through surveys, assessments, administrative records, performance monitoring systems, and digital information platforms. Descriptive statistical techniques provide practical methods for organizing and summarizing this information through frequency distributions, percentages, measures of central tendency, measures of variability, graphical presentations, and trend analyses. Effective application of descriptive statistics enables organizations to understand project performance, identify patterns and trends, monitor key performance indicators, measure outcomes, and generate reliable evidence that supports planning, resource allocation, policy development, and organizational learning.

This training adopts a highly practical and interactive learning approach that combines expert presentations, hands-on exercises, statistical software demonstrations, case studies, group assignments, and real-world analytical applications. Participants will gain practical experience in data management, descriptive analysis techniques, data visualization, dashboard development, interpretation of statistical outputs, and preparation of professional monitoring and evaluation reports. The course emphasizes practical applications of descriptive statistics within development projects, public health programs, education initiatives, humanitarian interventions, and organizational performance management systems.

Upon successful completion of this course, participants will possess the competencies required to manage datasets effectively, perform descriptive statistical analyses, interpret findings accurately, and communicate evidence professionally. The acquired knowledge and skills will enable organizations to strengthen monitoring and evaluation systems, improve reporting mechanisms, enhance evidence-based decision-making processes, support adaptive management practices, and maximize development outcomes through informed and data-driven interventions.

Course Objectives

1.     Understand the concepts and principles of descriptive statistics.

2.     Apply descriptive statistical methods in monitoring and evaluation systems.

3.     Organize and manage quantitative and qualitative datasets effectively.

4.     Calculate and interpret measures of central tendency and dispersion.

5.     Develop frequency distributions and cross-tabulations.

6.     Utilize charts, graphs, and tables for data presentation.

7.     Analyze trends and patterns in monitoring and evaluation data.

8.     Interpret descriptive statistical outputs accurately.

9.     Prepare evidence-based monitoring and evaluation reports.

10.  Strengthen data-driven decision-making and reporting capabilities.

Organizational Benefits

1.     Improved monitoring and evaluation reporting systems.

2.     Enhanced evidence-based decision-making processes.

3.     Strengthened data management and analytical capacities.

4.     Improved project performance monitoring and measurement.

5.     Enhanced reporting quality and stakeholder communication.

6.     Better identification of trends, patterns, and emerging issues.

7.     Improved organizational accountability and transparency.

8.     Strengthened planning and resource allocation processes.

9.     Enhanced organizational learning and knowledge management.

10.  Improved efficiency and effectiveness of development interventions.

Target Participants

This course is designed for Monitoring and Evaluation Officers, Project Managers, Program Managers, Researchers, Data Analysts, Statisticians, Information Management Officers, Government Officials, NGO Professionals, Humanitarian Program Managers, Development Practitioners, Planning Officers, Policy Analysts, Healthcare Information Officers, Donor-Funded Project Personnel, Consultants, Business Intelligence Specialists, Researchers, Academicians, and professionals responsible for data management, monitoring and evaluation, reporting, and evidence generation.

Course Outline

Module 1: Introduction to Descriptive Statistics and Monitoring and Evaluation

·       Concepts and principles of descriptive statistics

·       Role of descriptive statistics in monitoring and evaluation

·       Types of data and measurement scales

·       Variables and data classification techniques

·       Applications of descriptive statistics in development projects

·       Statistical thinking and evidence-based decision-making

Case Study: Applying descriptive statistics in monitoring community health interventions.

Module 2: Data Collection and Management for Statistical Analysis

·       Sources of monitoring and evaluation data

·       Data collection methodologies and techniques

·       Data coding and classification procedures

·       Data cleaning and validation techniques

·       Data storage and management systems

·       Data quality assurance principles

Case Study: Preparing project monitoring datasets for statistical reporting.

Module 3: Frequency Distributions and Tabulation Techniques

·       Principles of frequency distribution

·       Construction of frequency tables

·       Relative and cumulative frequencies

·       Cross-tabulation methodologies

·       Data summarization techniques

·       Interpretation of frequency distributions

Case Study: Analyzing beneficiary demographic profiles using frequency distributions.

Module 4: Measures of Central Tendency

·       Concepts of central tendency

·       Calculation of mean and weighted mean

·       Determination of median values

·       Identification and interpretation of mode

·       Comparison of central tendency measures

·       Practical applications in monitoring systems

Case Study: Measuring average project performance indicators across intervention areas.

Module 5: Measures of Dispersion and Variability

·       Concepts of variability and dispersion

·       Range and interquartile range calculations

·       Variance and standard deviation techniques

·       Coefficient of variation applications

·       Interpretation of measures of dispersion

·       Applications in monitoring and evaluation systems

Case Study: Assessing variability in educational performance indicators.

Module 6: Percentages, Ratios, and Proportions

·       Calculation of percentages and ratios

·       Proportion and rate analysis methodologies

·       Percentage change and growth analysis

·       Comparative statistical techniques

·       Indicator calculations and performance metrics

·       Interpretation of ratios and percentages

Case Study: Measuring service delivery coverage and program utilization rates.

Module 7: Data Visualization and Graphical Presentation

·       Principles of data visualization

·       Development of bar charts and histograms

·       Pie charts and frequency polygons

·       Line graphs and trend charts

·       Selection of appropriate graphical techniques

·       Interpretation of visual representations

Case Study: Designing project performance dashboards and monitoring charts.

Module 8: Trend Analysis and Time Series Presentation

·       Concepts of trend analysis

·       Time series data organization

·       Trend identification and interpretation

·       Comparative trend analysis techniques

·       Seasonal and periodic data patterns

·       Reporting and visualization of trends

Case Study: Monitoring trends in healthcare service utilization over time.

Module 9: Descriptive Analysis Using Statistical Software

·       Introduction to statistical software environments

·       Data entry and management procedures

·       Performing descriptive analyses

·       Generating tables and statistical summaries

·       Producing graphical outputs

·       Exporting and presenting analytical findings

Case Study: Conducting descriptive statistical analysis for donor-funded project reporting.

Module 10: Interpretation of Descriptive Statistical Outputs

·       Principles of statistical interpretation

·       Interpretation of tables and charts

·       Analysis of performance indicators

·       Identifying patterns and anomalies

·       Communicating analytical findings

·       Developing evidence-based conclusions

Case Study: Interpreting monitoring data for agricultural development programs.

Module 11: Reporting and Communicating Statistical Findings

·       Principles of statistical reporting

·       Development of monitoring reports and summaries

·       Data storytelling and communication techniques

·       Writing analytical narratives

·       Presentation of findings to stakeholders

·       Report quality assurance procedures

Case Study: Preparing comprehensive monitoring and evaluation performance reports.

Module 12: Applications of Descriptive Statistics in Monitoring and Evaluation

·       Descriptive statistics for project monitoring systems

·       Performance measurement and indicator tracking

·       Results-based management and reporting applications

·       Descriptive analysis in surveys and evaluations

·       Evidence generation for decision-making

·       Development of organizational analytical frameworks

Case Study: Designing an integrated descriptive statistical reporting system for monitoring, evaluating, and improving the performance and impact of multi-sector development 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.

 

 

Explore:

M&E Research & Data Analysis GIS & Remote Sensing ICT Skills Humanitarian Agriculture Business & Governance All Courses Download Training Calendar (PDF) Virtual / Online Training Courses Contact Us Subscribe Group Rates Gallery Trainer Consultancy

Ready to advance your career?

Join thousands of professionals from 30+ countries trained by FDC — classroom sessions across Africa, Middle East & Asia.

Browse All Courses Get Course Updates

Enquire

Captcha code Click image to refresh

training@fdc-k.org • +254 712 260 031 • Nairobi, Kenya