Data in the spotlight: International time series databanks
Date:
28/11/2024
Organised by:
University of Manchester
Presenter:
David Rawnsley
Level:
Entry (no or almost no prior knowledge)
Contact:
Emma Green
emma.green-3@manchester.ac.uk
Venue: Online
Description:
Are you wanting to understand how the world works? Have an interest in climate science, economy, trade, demographics, health or international development? Want to know about and how to access data from the IMF, World Bank, IEA, UN or OECD?
This free 90-minute online workshop will introduce you to the international time series data held by the UK Data Service. We’ll look at the range of socio-economic topics covered, explore some key datasets like the World Development Indicators and the IEA Renewable Energy Statistics, and cover how to access and download the data.
The workshop will consist of 30 minutes of presentations, 40 minutes of hands-on practical, and time at the end for questions.
Level: Introductory
Experience/knowledge required: Some spreadsheet knowledge would be useful
Target audience: Anyone interested in knowing more about the UK population
This event will be livestreamed on our UK Data Service YouTube channel but the chat will be disabled. By registering and attending the Zoom event you will be able to ask questions and interact.
Recordings of UK Data Service events are made available on our YouTube channel and, together with the slides, on our past events pages soon after the event has taken place.
This event is part of our UK Data Service introductory training series: Autumn 2024.
Cost:
Free
Website and registration:
Region:
Europe
Keywords:
Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis
Related publications and presentations from our eprints archive:
Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis