Training Course on 'Agricultural Statistics' in Sudan
Date: 23-27 October 2016
Venue: Khartoum - Sudan

In accordance with its 2016 Annual Work Plan and within the framework of Statistical Capacity Building (StatCaB) Programme, SESRIC organised the Training Course on 'Agricultural Statistics' at Central Bureau of Statistics (CBS) of Sudan on 23-27 October 2016.

The Training Course was conducted by Ms. Shadia J. ABU ALZAIN, Director of Agricultural Statistics Department at the Palestinian Central Bureau of Statistics of Palestine with the participation of 30 officials of CBS of Sudan.

As defined in the Classification of Statistical Activities (CSA Rev. 1 - October 2009;; Agriculture, forestry, fisheries – includes all agriculture, forestry and fishery related statistics, e.g. agricultural monetary statistics (agricultural economic accounts), agricultural structures (farm structure), trade in agricultural products, agricultural labour input, crop and animal production, agricultural commodities, agro-industry statistics (including food production and safety), organic farming and organic food, government expenditure for agriculture, fishing and forestry, products source and use tables, forest and forest product statistics, forest resource assessment and forest fire, trade in forest products, fisheries.

The Training Course on 'Agricultural Statistics' included discussion activities with a focus on the following topics:

  • Concept and importance of agricultural statistics
  • Structural statistics of the agricultural holdings
  • Production statistics (crops and livestock)
  • Agricultural national accounts
  • Trade statistics of agricultural products
  • Fisheries and aquaculture statistics
  • Forests and forests products statistics
  • Agricultural production inputs statistics
  • Samples and forms designing
  • Data collection methodology
  • Sources of data
  • Descriptive data
  • Classifications
  • Data processing and scrutinizing
  • Data dissemination, analysis and storage
  • Confidentiality of data
  • Quality of data
  • Agricultural census

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