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SPSS 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 13, 2026 52 dates
Dar es Salaam, Tanzania 10 days Jul 20, 2026 26 dates
Dubai, UAE 10 days Jul 20, 2026 52 dates
Istanbul, Turkey 10 days Oct 5, 2026 16 dates
Kampala, Uganda 10 days Jul 27, 2026 31 dates
Kigali, Rwanda 10 days Jul 20, 2026 52 dates
Kuala Lumpur, Malaysia 10 days Jul 20, 2026 31 dates
Mombasa, Kenya 10 days Jul 27, 2026 52 dates
Pretoria, South Africa 10 days Jul 20, 2026 52 dates
Singapore 10 days Jul 13, 2026 31 dates
Zanzibar, Tanzania 10 days Jul 13, 2026 16 dates

SPSS for Monitoring and Evaluation Training Course

Course Overview

The SPSS for Monitoring and Evaluation Training Course is a comprehensive professional development program designed to equip participants with the knowledge, methodologies, and practical competencies required to utilize Statistical Package for the Social Sciences (SPSS) for monitoring and evaluation, research, project management, performance measurement, and evidence-based decision-making. In today's data-driven development environment, governments, donor agencies, non-governmental organizations, humanitarian institutions, healthcare organizations, academic institutions, and private sector entities increasingly depend on statistical analysis and data-driven insights to assess project performance, measure outcomes and impacts, evaluate interventions, and formulate strategic policies and programs. This course provides participants with practical approaches for managing, analyzing, interpreting, and reporting monitoring and evaluation data using SPSS.

Monitoring and evaluation systems generate large volumes of quantitative and qualitative data that require systematic management and analysis to produce reliable evidence for planning and decision-making. SPSS is one of the world's most widely used statistical software applications for data management, descriptive statistics, inferential analysis, survey data processing, impact assessment, and performance reporting. Effective utilization of SPSS requires a sound understanding of research methodologies, data collection systems, statistical concepts, data quality assurance principles, and reporting frameworks. This course introduces participants to internationally recognized concepts and best practices in data management, statistical analysis, monitoring and evaluation methodologies, and evidence generation using SPSS technologies.

The training emphasizes practical application and experiential learning through simulations, demonstrations, hands-on exercises, case studies, and group assignments. Participants will gain practical experience in designing databases, importing and cleaning data, managing variables, conducting descriptive and inferential statistical analyses, developing monitoring and evaluation indicators, performing baseline and endline comparisons, generating charts and dashboards, and preparing analytical reports. The course also explores advanced analytical techniques including regression analysis, hypothesis testing, cross-tabulations, impact evaluation methods, and data visualization approaches that support organizational learning and strategic decision-making.

Upon successful completion of this course, participants will possess the competencies necessary to effectively utilize SPSS for data management, statistical analysis, monitoring and evaluation, and evidence generation. The knowledge and practical skills acquired through this training will enable professionals to strengthen monitoring and evaluation systems, improve data quality and reporting, enhance accountability and transparency mechanisms, optimize project performance, and contribute to sustainable development outcomes and organizational excellence.

Course Objectives

1.     Understand the concepts, principles, and applications of SPSS in monitoring and evaluation systems.

2.     Design and manage databases and datasets using SPSS software.

3.     Import, clean, code, and validate monitoring and evaluation data effectively.

4.     Apply descriptive statistical techniques for data analysis and reporting.

5.     Conduct inferential statistical analyses and hypothesis testing using SPSS.

6.     Analyze baseline, midline, and endline survey data using statistical methodologies.

7.     Develop monitoring and evaluation indicators and performance measurement systems.

8.     Generate tables, charts, dashboards, and visualizations for reporting purposes.

9.     Interpret statistical findings and prepare evidence-based reports and recommendations.

10.  Strengthen organizational decision-making through effective data analysis and evidence generation.

Organizational Benefits

1.     Improved data management and information processing capabilities.

2.     Enhanced monitoring and evaluation and reporting systems.

3.     Strengthened evidence-based planning and strategic decision-making processes.

4.     Improved project performance measurement and impact assessment capabilities.

5.     Enhanced data quality assurance and information reliability.

6.     Increased efficiency in data analysis and reporting processes.

7.     Strengthened accountability and transparency mechanisms.

8.     Improved donor reporting and compliance with monitoring requirements.

9.     Enhanced organizational learning and knowledge management practices.

10.  Improved project performance and sustainable development outcomes.

Target Participants

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

Course Outline

Module 1: Introduction to SPSS and Monitoring and Evaluation Concepts

·       Concepts and principles of monitoring and evaluation and statistical analysis

·       Overview of SPSS software and applications in monitoring and evaluation

·       Understanding the SPSS interface and workspace

·       Data types, variables, and measurement scales

·       Applications of SPSS in project monitoring and impact evaluation

·       International standards and best practices in data analysis and evidence generation

Case Study: Designing an SPSS-based monitoring and evaluation framework for a community health intervention project.

Module 2: Data Entry, Importation, and Database Management

·       Creating datasets and defining variables in SPSS

·       Importing data from Excel and other databases

·       Variable coding and labeling procedures

·       Data transformation and recoding techniques

·       Managing missing values and duplicate observations

·       Database organization and documentation practices

Case Study: Developing an SPSS database for education sector performance monitoring.

Module 3: Data Cleaning and Quality Assurance

·       Principles of data quality management and assurance

·       Identification and management of data inconsistencies and errors

·       Validation and verification procedures

·       Data editing and correction methodologies

·       Management of outliers and missing data

·       Preparation of datasets for statistical analysis

Case Study: Conducting data quality assessments for donor-funded household survey datasets.

Module 4: Descriptive Statistical Analysis

·       Frequency distributions and summary statistics

·       Measures of central tendency and dispersion

·       Cross-tabulations and contingency tables

·       Data summarization and interpretation techniques

·       Development of statistical tables and charts

·       Preparation of descriptive analytical reports

Case Study: Analyzing baseline survey data for agricultural productivity monitoring programs.

Module 5: Data Visualization and Reporting

·       Principles of data visualization and information presentation

·       Development of charts, graphs, and dashboards

·       Presentation of monitoring indicators and performance trends

·       Generation of automated reports and statistical outputs

·       Interpretation of visual analytical findings

·       Communication of monitoring and evaluation results

Case Study: Preparing graphical monitoring reports for nutrition and food security programs.

Module 6: Inferential Statistics and Hypothesis Testing

·       Introduction to inferential statistical methodologies

·       Confidence intervals and significance testing procedures

·       Chi-square tests and association analyses

·       Correlation and comparative analyses

·       Interpretation of statistical significance and findings

·       Reporting inferential statistical outputs

Case Study: Testing relationships between training interventions and project outcomes.

Module 7: Regression and Predictive Analysis

·       Concepts and principles of regression analysis

·       Simple and multiple regression techniques

·       Model development and interpretation procedures

·       Predictive analytics and forecasting methodologies

·       Identification of factors influencing project outcomes

·       Preparation of regression reports and recommendations

Case Study: Predicting determinants of household food security using survey data.

Module 8: Baseline, Midline, and Endline Survey Analysis

·       Concepts and applications of survey evaluations

·       Management of baseline and endline datasets

·       Comparative analysis techniques and methodologies

·       Measurement of project outcomes and impacts

·       Trend analysis and performance assessment procedures

·       Interpretation and reporting of survey findings

Case Study: Evaluating changes in educational outcomes between baseline and endline surveys.

Module 9: Monitoring and Evaluation Indicator Analysis

·       Development and measurement of key performance indicators

·       Indicator tracking and performance monitoring methodologies

·       Analysis of output, outcome, and impact indicators

·       Development of indicator dashboards and scorecards

·       Reporting of monitoring performance trends

·       Utilization of indicators for adaptive management

Case Study: Developing indicator tracking systems for maternal and child health programs.

Module 10: Impact Evaluation and Performance Assessment

·       Principles of impact evaluation and performance measurement

·       Statistical approaches for impact assessment

·       Comparative and longitudinal analyses

·       Measurement of intervention effectiveness and efficiency

·       Interpretation of evaluation findings and recommendations

·       Preparation of impact assessment reports

Case Study: Assessing the effectiveness of livelihood improvement interventions using SPSS.

Module 11: Advanced Data Analysis Techniques

·       Multivariate analysis and advanced analytical methodologies

·       Composite index construction and analysis techniques

·       Data segmentation and profiling methodologies

·       Analytical modeling and decision-support systems

·       Integration of analytical outputs into organizational planning processes

·       Utilization of advanced analytics for evidence generation

Case Study: Developing vulnerability indices for social protection and resilience programs.

Module 12: Capstone Project and Organizational Application of SPSS

·       Development of complete monitoring and evaluation analytical projects

·       Integration of SPSS analysis into organizational information systems

·       Preparation and presentation of analytical reports

·       Development of action plans and evidence-based recommendations

·       Organizational adoption and institutionalization of analytical systems

·       Future trends and innovations in statistical analysis and monitoring technologies

Case Study: Designing a comprehensive SPSS-based monitoring and evaluation system for multi-sector development projects.

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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