Getting More Done – Becoming a more efficient, effective and maybe happier researcher (few places remaining)

Date:

15/12/2020

Organised by:

The University of Edinburgh

Presenter:

Professor Vernon Gayle, Co-Director of the ESRC National Centre for Research Methods.
Professor of Sociology and Social Statistics at the University of Edinburgh.

Level:

Entry (no or almost no prior knowledge)

Contact:

Laura Marshall
0131 651 3001
L.marshal@ed.ac.uk
Working week: Monday - Wednesday

video conference logo

Venue: Online

Description:

Getting More Done – improving your workflow and becoming a more efficient, effective and potentially happier researcher

Many researchers at different career stages report that they would like to get more done. At the current time it is not possible to expand time. It is however possible to improve your data analysis workflow in order to become a more efficient, effective and potentially happier researcher.

This is a one-day course on improving your data analysis workflow. It will introduce to key concept in organising the data analysis workflow and improving effectiveness and efficiency.

It is most suited to empirical social science researchers.

Course Timings: 11:00 - 16:00 and will be delivered on-line

Cost:

The online fee per teaching day is:

• £30 per day for UK/EU registered students
• £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions.
• £100 per day for all other participants

All fees include event materials

Cancellation Policy: Please be reminded that you will be charged the full registration fee if you cancel your place within 4 weeks before the training delivery date or you fail to attend.

If you are able to fill the place on the course you are cancelling then the cancellation charge will not apply.

Website and registration:

Region:

Scotland

Keywords:

Quantitative Data Handling and Data Analysis, Data Analysis Workflow

Related publications and presentations:

Quantitative Data Handling and Data Analysis

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