Survey Design and Data Quality - In Person

The course aims to provide participants with an understanding of the key issues involved in the design, implementation and analysis of sample surveys, with particular emphasis on sample design, data collection procedures, non-response, questionnaire design and testing, and the handling of missing data. Participants will gain practical insights into survey design and management, as well as the strengths and limitations of probability-based and non-probability-based surveys.

The course is designed for a broad range of professionals, including data analysts working across different disciplinary fields, government analysts, policy professionals, survey designers, researchers and PhD students. It will be particularly valuable for anyone involved in analysing survey data, designing or commissioning surveys, interpreting survey findings, or developing policies and making decisions that rely on statistical analysis of survey data. The course will help participants critically assess survey quality, understand the limitations of survey evidence and make more informed use of survey data in research, policy development and practice.

The course covers: 

• Total Survey Error Framework

• Survey sampling

• Survey non-response

• Probability-based vs non-probability-based surveys

• Survey mode

• Questionnaire design and testing

By the end of the course participants will:

• Demonstrate understanding of the key principles and practices involved in survey design, implementation and data analysis.
• Explain and evaluate the principles of questionnaire design and testing, drawing on relevant survey methodology literature and best practice.
• Identify, describe and critically evaluate a range of sampling designs, including probability-based and non-probability-based surveys, and understand their respective strengths and limitations.
• Identify and evaluate potential sources of survey error, including issues relating to sampling, non-response and data collection, and understand approaches to assessing and minimising their impact on survey quality.
• Demonstrate understanding of approaches to identifying and handling missing data in survey analysis, and assess their implications for the interpretation of survey findings.
• Critically assess the quality, limitations and suitability of survey data for particular research questions, policy development and decision-making.
• Interpret survey findings critically and understand the implications of survey design and data quality for statistical analysis and evidence-based policy.

Target Audience

The course is designed for a broad range of professionals, including data analysts working across different disciplinary fields, government analysts, policy professionals, survey designers, researchers and PhD students. It will be particularly valuable for anyone involved in analysing survey data, designing or commissioning surveys, interpreting survey findings, or developing policies and making decisions that rely on statistical analysis of survey data.

THIS COURSE WILL TAKE PLACE ON 24 MAY (10:00-17:00), 25 MAY (9:00-17:00) AND 26 MAY (09:00-16:00) AND EQUATES TO THREE TEACHING DAYS FOR PAYMENT PURPOSES.