Training Course on Impact Evaluation and Data Analysis using SPSS

Training Course on Impact Evaluation and Data Analysis Using SPSS

Introduction

The ability to evaluate the impact of programs, policies, or interventions is crucial for organizations aiming to measure effectiveness and drive improvements. The Impact Evaluation and Data Analysis Using SPSS training course is designed to provide professionals with the essential skills to conduct rigorous impact evaluations and analyze data using SPSS, one of the most widely used statistical software tools. Training Course on Impact Evaluation and Data Analysis Using SPSS offers hands-on training in collecting, analyzing, and interpreting data to assess the success of various projects and initiatives.

Impact evaluations play a critical role in assessing the effectiveness of programs by determining their outcomes and understanding the factors driving success or failure. SPSS offers a comprehensive suite of statistical tools that are ideal for evaluating data and drawing meaningful insights. This course will guide participants through the entire process of impact evaluation, from designing evaluation frameworks to analyzing data and reporting results. By learning how to leverage SPSS for data analysis, participants will enhance their ability to make informed, data-driven decisions in any organizational context.

Through a combination of practical examples and case studies, participants will gain valuable experience in using SPSS to analyze both qualitative and quantitative data. This course will help participants understand the intricacies of different evaluation designs, data collection methods, and statistical techniques that are central to impact evaluation. Real-world case studies will provide insight into the best practices in conducting impact evaluations across diverse sectors, including education, health, and social development.

Course Duration

5 Days

Course Objectives

1. Understand the fundamentals of impact evaluation and its role in program assessment.
2. Learn the core principles of statistical data analysis using SPSS.
3. Gain practical skills in designing impact evaluations and selecting appropriate evaluation methodologies.
4. Master data collection techniques for both qualitative and quantitative data.
5. Learn how to clean and prepare data for analysis in SPSS.
6. Apply various statistical tests and techniques in SPSS to analyze impact data.
7. Interpret the results of impact evaluations and present findings effectively.
8. Understand how to manage and analyze large datasets using SPSS.
9. Examine ethical considerations in impact evaluation and data analysis.
10. Explore real-world case studies to understand the application of impact evaluation in diverse sectors.

Organizational Benefits

1. Improve their ability to assess the effectiveness of their programs and interventions.
2. Build internal capacity for conducting impact evaluations and data analysis.
3. Gain insights into program strengths and weaknesses, leading to better decision-making.
4. Develop data-driven strategies for program improvement and scaling.
5. Enhance the quality and rigor of evaluations, ensuring more reliable results.
6. Improve reporting capabilities and demonstrate program success to stakeholders.
7. Develop a culture of evidence-based decision-making and continuous improvement.
8. Strengthen the monitoring and evaluation (M&E) function within the organization.
9. Optimize resource allocation by identifying high-impact programs and interventions.
10. Foster organizational transparency by using data to communicate program results effectively.

Target Participants

• Researchers and data analysts
• Monitoring and Evaluation (M&E) professionals
• Program managers and coordinators
• Policy analysts and development experts
• Government officials and public administrators
• Consultants in the development sector
• Academics and students in social sciences, economics, and related fields
• Non-governmental organization (NGO) staff involved in program evaluation
• Corporate professionals interested in performance measurement and evaluation
• Anyone involved in data-driven decision-making and impact assessments.

Course Outline

Module 1: Introduction to Impact Evaluation and SPSS

1. Overview of impact evaluation concepts and methodologies.
2. The importance of evidence-based decision-making.
3. Introduction to SPSS: Features, interface, and functions.
4. Understanding different types of evaluation designs (randomized controlled trials, quasi-experimental designs).
5. Case Study: An impact evaluation of a health intervention in sub-Saharan Africa.

Module 2: Designing Impact Evaluations

1. Setting clear objectives and indicators for impact evaluations.
2. Choosing the right evaluation design: Experimental vs. non-experimental.
3. Sampling techniques and ensuring data quality.
4. Developing a theory of change and logical framework.
5. Case Study: Designing an education program evaluation in a low-income country.

Module 3: Data Collection and Preparation for Analysis

1. Identifying data sources: Surveys, interviews, and administrative data.
2. Data cleaning techniques in SPSS: Handling missing values and outliers.
3. Data transformation and recoding in SPSS.
4. Preparing datasets for analysis (merging datasets, coding variables).
5. Case Study: Collecting data for a community health impact evaluation.

Module 4: Statistical Analysis Using SPSS

1. Descriptive statistics: Summarizing data and understanding distribution.
2. Bivariate analysis: Correlation and regression techniques.
3. Conducting t-tests, ANOVA, and chi-square tests in SPSS.
4. Understanding and performing multivariate regression analysis.
5. Case Study: Analyzing the impact of a microfinance program using SPSS.

Module 5: Interpreting and Reporting Impact Evaluation Results

1. Understanding statistical significance and confidence intervals.
2. Presenting results in clear, actionable formats.
3. How to write an evaluation report with clear recommendations.
4. Visualizing results with SPSS graphs and tables.
5. Case Study: Reporting the findings of a water sanitation program evaluation.

Module 6: Ethical Considerations and Real-World Applications

1. Ethical challenges in impact evaluation and data analysis.
2. Ensuring transparency and integrity in data analysis.
3. Applying impact evaluation findings to program improvement.
4. Limitations of impact evaluations and generalizing results.
5. Case Study: Ethical dilemmas in evaluating social welfare programs.

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.