Survey Quality in Quantitative Social Science Research

2025/2026

Academic Year

ENG

Instruction in English

Delivered at:

Department of Sociology

Course type:

Elective course

When:

4 year, 1, 2 module

Instructor

Lebedev, Daniil

Course Syllabus

Abstract

The process of conducting quantitative research in social sciences requires making numerous methodological decisions, each of which can impact data quality and the overall validity and reliability of a study. This course explores key theoretical and methodological aspects of survey quality, as well as practical applications of survey quality assessment. As the variety of available quantitative data sources continues to grow, ensuring high data quality becomes increasingly important. Proper assessment and transparent reporting of survey quality contribute to research reproducibility, replicability, and overall reliability. The course introduces widely used survey quality frameworks, including Total Survey Error (TSE) and Total Survey Quality (TSQ), and demonstrates their application in real-world research scenarios. This course is particularly beneficial for students planning to conduct quantitative research. It provides essential tools for designing robust studies and ensuring high-quality data collection. Students will learn how to mitigate potential quality issues in their own research and critically assess the quality of existing quantitative studies.

Learning Objectives

• To develop students' systematic understanding of the theoretical and methodological aspects of the quality of quantitative research, as well as practical skills for evaluating and ensuring the quality of their own research.

Expected Learning Outcomes

• Explain the basic concepts of validity and reliability in quantitative research.
• Distinguish between systematic and random errors, understand their sources and impact on results.
• Describe the structure of the Total Survey Error (TSE) concept and its key components.
• Define Total Survey Quality (TSQ) approaches and be able to apply them to assess data quality.
• Interpret cognitive models of answering a question.
• Distinguish and describe data quality indicators.
• Use data quality indicators to assess the reliability and validity of research.
• Compare different data collection methods (face-to-face, telephone interviews, online surveys, non-reactive data collection methods) based on quality criteria.
• Evaluate the strengths and weaknesses of the chosen data collection method.
• Explain what representativeness is and identify coverage and sampling errors.
• Evaluate and interpret sampling error and its impact on representativeness.
• Identify sources of measurement error and explain how they affect research results.
• Perform practical data quality diagnostics in real or educational cases.
• Distinguish between the concepts of reproducibility and replicability.
• Critically evaluate the quality of published studies in terms of transparency, replicability, and data quality.
• Plan own research taking into account the principles of ensuring high data quality, as well as reproducibility and replicability.

Course Contents

• Validity, reliability and sources of error in quantitative social science research
• Total Survey Error and Total Survey Quality frameworks
• Cognitive models of respondents' answers to questions
• Data quality indicators in quantitative social science research
• Data quality and data collection modes
• Representativeness of research: coverage and sampling error
• Measurement error: quality of data collection tools
• Replicability and reproducibility

Assessment Elements

• Activity
• Essay
• Final Assignment

Interim Assessment

• 2025/2026 2nd module
  0.15 * Activity + 0.15 * Activity + 0.35 * Essay + 0.35 * Final Assignment

Bibliography

Recommended Core Bibliography

• Методы социологического исследования : Учеб. пособие, Девятко, И.Ф., 2009

Recommended Additional Bibliography

• Measurement error : consequences, applications and solutions, , 2009
• Survey errors and survey costs, Groves, R. M., 2004
• Модели объяснения и логика социологического исследования, Девятко, И. Ф., 1996
• Основы построения выборки для социологических исследований, Чуриков, А. В., 2020

Authors

• DYMOVA POLINA MAKSIMOVNA