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The role of a statisticians when working with scientists

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Presentation on theme: "The role of a statisticians when working with scientists"— Presentation transcript:

1 The role of a statisticians when working with scientists
Challenges and opportunities

2 Statistics for Sustainable Development
A not-for-profit, social enterprise providing technical support to development initiatives Carlos Barahona |

3 What do you want to do when you finish your MSc?
Pathways to a professional carrier…. This Photo by Unknown Author is licensed under CC BY-SA

4 What do we learn while training as statisticians?

5 Components of an applied statistician’s toolbox
Personal communication. Ric Coe (Statistics for Sustainable Development)

6 Components of an applied statistician’s toolbox
Personal communication. Ric Coe (Statistics for Sustainable Development)

7 Components of an applied statistician’s toolbox
The text said something about how the grey area is focus on traditional stats courses. Enlightened ‘modern’ courses started expanding to the blue area. The best courses work on whole of the right hand column. But the green area is what applied statisticians really need, along with understanding the basics of everything in the table. The other point from it is that occasionally an individual fills the roles of both scientists and statistician but it is rare.    If you are a more common type of statistician then you can only do a good job when working with scientists and that requires communication and negotiation etc skills along with the technical stuff. Personal communication. Ric Coe (Statistics for Sustainable Development)

8 A diagram of research support functions in a scientific research institute

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10 Potential roles of a statistician in a scientific team
Support Partnership Leadership Potential roles of a statistician in a scientific team

11 What additional tools and skills are useful?
Concepts Systems Language Specific scientific knowledge Size: from small to large ( ≠ big data) Structure: simple to complex Location: local to global Quality: quality control to quality assurance Data-to-information loops Data skills What additional tools and skills are useful?

12 Consultancy skills Listen Ability to ask good questions
Systems thinking Adapt and apply Negotiation skills Bridging And if you can…be a good writer Consultancy skills

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14 Research methods and agroecological intensification
Requires Systems perspective Integrating social and biophysical research Using mixed qualitative and quantitative methods Approaches and methods conditioned by Values of the program Local context Local capacity … and objectives [ccrp.org]

15 What can we contribute to the teams we work with?
Sifting signal from noise Efficiency Visualisation and interpretation Quality assurance Cross-disciplinary synergies What can we contribute to the teams we work with?

16 Verbs and nouns Methods and topics

17 Thanks


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