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ANICANET Summer School 2017

Within the framework of the ANICANET project a Summer School entitled "Quantitative analysis of animal husbandry in Central Asia" takes place in Halle (Saale), Germany, from 25 to 29 September 2017.

IAMO is pleased to invite applicants to a summer school on quantitative analysis of animal husbandry in Central Asia to be organized in the framework of a new project "Revitalising animal husbandry in Central Asia: A five-country analysis (ANICANET)" supported by the Federal Ministry of Education and Research (BMBF). The ANICANET project aims at gaining empirically founded insights into strategies stimulating the revitalisation of livestock husbandry in the five Central Asian countries. It emphasises quantitative data collection across countries and the promotion of research capacity in Central Asia.
The Summer School will combine theoretical lectures and practical exercises with discussion sessions on current issues of animal husbandry in Central Asia. The participants will gain competency in using statistical software for analysing agricultural survey data and are expected to prepare and present a research project on a pertinent livestock development topic based on exemplary micro-data made available by the summer school instructors. For the practical exercises in data analysis, the participants will be introduced to methods in Stata. Sessions will include lectures, discussions, group work, case study exercises and statistical analysis. The summer school is open to any student interested in issues of livestock developments that are related to Central Asia. Participants from the five post-Soviet Central Asian countries Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan are particularly welcome.

Unfortunately the application deadline has now expired.

ANICANET Summer School
"Quantitative analysis of animal husbandry in Central Asia"
25-29 September 2017
Halle (Saale), Germany
anicanet(at)iamo.de


Contact

Dr. Nodir Djanibekov

Dr. Nodir Djanibekov

Research Associate
Room: 119

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