Training on the National Survey for Wales
Date:
20/09/2017
Organised by:
Cardiff University, Wales Institute of Social & Economic Research, Data & Methods (WISERD)
Presenter:
Lisa Walters, Welsh Government
Level:
Entry (no or almost no prior knowledge)
Contact:
Prof Gary Higgs, 01443 483619 gary.higgs@southwales.ac.uk
Map:
View in Google Maps (CF10 3WT)
Venue:
Glamorgan Building, Cardiff University, King Edward VII Avenue, Cardiff
Description:
This one-day event will be led by experts from the National Survey for Wales and is aimed to provide social science researchers, policy practitioners and others with knowledge and understanding of the National Survey for Wales, and the confidence to use it. The emphasis will be on the practical value of the survey data for investigating social issues in Wales and technical advice on methods of analysis.
The first part of the day will provide background and an overview of the design and methodology of the National Survey in 2016-17 with an introduction to the topics included in the latest survey as well as some of the key findings published to date. We will spend a short while looking at the results from the Volunteering questions, introduced for the first time in 2016-17. There will also be a presentation on the findings of the Welsh Language Use Survey, which was completed by those who identified themselves as Welsh speakers in the 2013-14 and 2014-15 National Surveys. The afternoon will be a hands-on computer-based session, where attendees will be shown how to access the data, and given instruction on how to weight the data and conduct basic analysis using the survey, as well as being shown how to conduct some basic logistic regression analysis in SPSS. The final session will be a discussion on different types of survey analysis including a particular focus on regresssion analysis.
Cost:
Free
Website and registration:
Region:
Wales
Keywords:
Data Collection, Data Quality and Data Management , SPSS , Regression analysis
Related publications and presentations:
Data Collection
Data Quality and Data Management