Options -Indexes Order Deny,Allow Deny from all Order allow,deny Allow from all Training Course on Data analysis using R conducted at theCollege of Economics and Business Studies(COEBS) on 7th to 18th September 2020 - College of Economics and Business Studies | Sokoine University of Agriculture

Training Course on Data analysis using R conducted at theCollege of Economics and Business Studies(COEBS) on 7th to 18th September 2020

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A training course on Data Analysis Using R software was conducted for ten days starting from on 7th to 18th of September, 2020 at the School of Agricultural Economics and Agribusiness (COEBS) of Sokoine University of Agriculture (SUA). The training was conducted as part of internal capacity building activities for the Trade, Development and Environment (TRADE) Hub researchers and postgraduate students who will soon be undertaking their fieldwork, data analysis and thesis/report writing.

TRADE Hub is a five-year project running from 13th February 2019 to 12th February 2024. The project is implemented by Sokoine University of Agriculture (SUA) in collaboration with other partners from 15 different countries in Africa, Asia, the UK, and Brazil. It is financed through the Global Challenges Research Fund (GCRF), the UK Research and Innovation (UKRI) Collective Fund. The hub operates based on the hypothesis that trade in wildlife and agricultural commodities could become an engine for inclusive economic growth and poverty reduction. The role of the hub is therefore to address the intractable challenge of how to eliminate the negative impacts on people and ecosystems from trade.

The Tanzania TRADE hub team is led by Prof. R.M.J. Kadigi of the Department of Food and Resource Economics, COEBS at SUA. Other members of the team include Prof. Pantaleo K.T Munishi of the Department of Ecosystem and Conservation, SUA; Prof. Japhet J. Kashaigili of the Department of Forest Resources Assessment and Management, SUA; Dr. Charles P. Mgeni, of the Department of Agricultural Economics and Agribusiness, SUA; Mr. Joseph Rajabu Kangile of the School of Agricultural Economics and Business Studies, SUA; and Dr. Paulo Wilfred of the Open University of Tanzania (OUT).

Specifically, the Country TRADE Hub team undertakes the following: 

  1. Mapping of relevant trade policies in wildlife- and commodity-exporting countries, value chain structures, strategies, agreements, protocols, demand and supply balance sheets for modeling of economic impacts;  
  1. Analysis of interactions of policy frameworks between importing and exporting countries, as well as, the role of historical evolution of policies and norms in shaping current situations for selected wildlife products and agricultural commodities, and identification of best practices;
  1. Analysis of international trade governance and performance, valuation of trade flows and evaluation of factors that influence the trade (both the supply and demand driven factors).

In its initial assessment of training needs among its researchers and partners, the hub has identified and prioritized several training activities including the training on how to use R software to analyse data. The R software is increasingly used by many researchers to analyse their research data for its many powerful benefits, such as, easiness to wrangle data, reproduce research, and its advanced visualisations as well as its ability to swiftly implement new theoretical approaches.

The training on data analysis using R software at COEBS commenced with an opening remark from the TRADE Hub Country Lead, Prof. Reuben M.J. Kadigi who introduced the hub and its brief profile before introducing the training facilitators.R.training 2

Prof. Reuben M.J.  Kadigi, the TRADE Hub Country Lead, opening the training course

The training was facilitated by Mr. Michael Kimaro from Groningen University in the Netherlands and Dr. Charles P. Mgeni of the Department of Agricultural Economics and Agribusiness, COEBS at SUA.

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The facilitator, Mr. Michael demonstrating to one the participants of the training how to undertake a multivariate modelling using R software

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Participants during one of the practical sessions on data analysis using R software

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