This course aims to develop knowledge and skills related to the data collection, processing, tabulation, analysis, and dissemination of survey data in general and post-harvest loss surveys in particular. This is critical for informed decision-making in various sectors such as agriculture, education, and health. The reduction of post-harvest losses (PHL), for instance, has been identified as a priority area for sustainable development goals (SDG) due to its importance in food security and agricultural productivity.

In the context of improving national capacities to produce statistical data, this course integrates traditional survey methods with innovations to enhance accuracy, timeliness, and efficiency. The course draws on lessons from field activities in countries such as Namibia, Mali, Malawi, and Zimbabwe and applies these to broader contexts. The intended audience includes survey managers, field workers, statisticians, and policymakers who aim to leverage data for national planning and reporting on SDGs.