For 20 years, QED Group’s work has been focused on promoting data-driven decision-making and employing innovative data collection methods in our projects.  In Afghanistan, our data collectors used GPS-enabled phones to verify collectors’ presence at the verification sites. We also developed a unique and secure cloud server with a master database that pulled collected data used a Structured Query Language that enabled users to analyze data. QED Group brings extensive experience in advanced analytic methods and statistics, predictive analytics, and linear and multivariate regression analysis.  QED Group’s staff also have immense experience and capabilities with statistical methods and programming skills such as R, Python, SPSS, SAS, STATA and qualitative software such as Dedoose, NVIVO, and MaxQDA.


In 2017, QED Group’s Data Hub team completed an analysis of Uganda’s Sustainable Comprehensive Responses for Vulnerable Children and Their Families (SCORE) data to study the impact of interventions on various households across time. We profiled and clustered households using data from this project to measure the impact of project interventions. We then created an Intervention Impact Model using “step-wise regression” methodology on R-Studio to look at which interventions work and which do not to improve the vulnerable Households in Uganda.
  • Data Wrangling: QED Group is an expert in data wrangling and simplifies it by collating data from a large number of sources and systematically files it for easy accessibility, understandability and analysis.
  • Related Project: Uganda’s Agricultural and Animal Husbandry Census
For Uganda’s Agricultural and Animal Husbandry Census , the QED Group staff created a script to pull data from more than 900 documents from census, government reports and other sources. The pulled data was then stored in the form of an Excel tabular format for easy and efficient analysis.