In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.
This interface allows you to search for statistical classifications, guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources. You can search by SUBJECT (general, agriculture, forestry, fishery and aquaculture, and natural resources) or use the ADVANCED SEARCH to search by keyword, country, language and lead authoring unit/office. Comments, suggestions and inquiries can be addressed to: [email protected].
You can access here all the statistical guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources.
Type a keyword in the free text search box or refine your search by keyword, country, language and lead authoring unit/office.
Comments, suggestions and inquiries can be addressed to: [email protected].
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know how to create a questionnaire; b) Know the major question types (text, numeric, date, single and multi answer, list); c) Understand the concept for enablement conditions; d) Be familiar with the fields to be completed for questions; and e) Know about static text.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know what validation conditions and messages are; and b) Apply basic C# syntax for creating validation and enablement conditions.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know how to build a roster; b) Know about nesting rosters; c) Know about html tags; and, d) Know about piping.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will give an overview of the interview application.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will give an overview of data export.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. This training session will provide an overview of: Tablet management; Tablet configuration; Useful apps and Equipment/Accessories.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts. At the end of this session, the audience will: a) Know the difference between Administrator, HQ, and Supervisor; b) Be familiar with workflow of Survey Solutions and events in the life a case; c) Know how to access HQ and Supervisor; d) HQ primary functions (create Supervisor, Interviewers, Import Template, Create Cases, Assign Cases to Supervisor); e) Supervisor primary functions (assign cases to Interviewers); f) Use HQ and Supervisor to approve/reject completed cases; f) Know about creating field reports with HQ and Supervisor.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this material for in-classroom training on the use of CAPI for agricultural surveys targets decision makers, survey managers, questionnaire designers, trainers of field staff and data analysts.
Lead authoring unit/office: Statistics Division (ESS)
