Collecting quantitative data

Quantitative research focuses on collecting numerical data or data that can be conceptualized on a numeric scale. Researchers in agriculture, food systems, nutrition, and health use a variety of methods and tools for collecting quantitative data. Below you will find resources and guidance for various approaches to quantitative data collection.

 

 

Survey data collection

 

SCANR tip: "Field research" or "field surveys" refer to research done in a natural setting, such as a survey of participants living in a community of interest. In contrast, lab research is conducted in a controlled environment. 

 
Anthropometric measurements

 

  • Best practices for quality anthropometric data collection at the DHS program: This guide from the USAID DHS program explains best practices for collection of anthropometric data, including sampling, equipment, team composition, field worker training, standardization, supervision, quality assurance, and dissemination. 
  • DAPA measurement toolkit: This toolkit from the Cambridge Biomedical Research Centre introduces the types of anthropometric measurements and describes related indices and methods. 
  • FANTA guide to anthropometry: This guide from USAID's FANTA project explains anthropometric measurements and indices, as well as the nutrition conditions typically assessed in different demographic groups. The guide also discusses how to interpret anthropometric data and offers guidance for selecting equipment and taking measurements in low-resources settings. 
 
Lab-in-the-field experiments

 

 
Special topic: time use

 

Measuring how people allocate their time can be very challenging. Below are some resources on how to measure time use. Are there other special topics in data collection that you would like SCANR to explore? Post in our Forum or email [email protected].

 

 

Last update: 19 August 2022