Content

This course is an introduction to the principles and practice of survey design. The main contributions of the research in Survey Methodology are reviewed on the factors that affect the quality of the surveys.

This subject aims to combine the theoretical perspective with the development of applied skills to design and carry out surveys. Using the phases of the survey process as a common thread, the different sources of error will be presented following the perspective of the Total Survey Error, as well as the ways to mitigate it. . The concept of error will be used as a framework to discuss the consequences of using different methods of data collection, the coverage capacity of the sampling frames, alternative sampling designs and their impact on the standard errors of the survey statisticians, the effects of the design of the questionnaire as an instrument of measurement (impact of the order of the questions, differences in its wording, among others), the supervision systems of the field work, the role of the interviewer and the respondent, the impact of the non-response in the statistics of the survey, or the treatment and analysis of the data obtained. The design of surveys implies taking a set of decisions making an adequate balance between the research objectives, the survey errors, the economic costs, and the calendar restrictions that they entail.

Module 1: Defining a project
										
											1. Definition of a survey
										
											1.1 A little history: The origins of surveys
										
											1.2 The private sector in Spain
										
											1.3 Some working methodologies for data collection
										
											1.4 Some essential characteristics of surveys
										
											1.5 Strengths and weaknesses of surveys
										
											2. Types of surveys. Phases of a survey and definition of a project
										
											2.1 Types of surveys
										
											2.2 Phases of a survey
										
											2.3. Definition of a project
										
											3. Choice of the information collection method
										
											3.1 Classification of information collection methodologies
										
											3.2 Choice of the information collection method
										
											4. The sample design
										
											4.1 Delimitation of the study universe
										
											4.2 Determination of the sampling frame
										
											4.3 The sampling procedure
										
											4.4 The sample size
										
											5. Sampling error, confidence intervals and weighting
										
											5.1 Sampling error
										
											5.2 Confidence intervals
										
											5.3 Weighting

Module 2: Questionnaire design and fieldwork
										
											6. Questionnaire design
										
											6.1 Operationalization of concepts
										
											6.2 Question construction
										
											6.3 Recommendations when writing questions
										
											6.4 Types of survey error
										
											7. Types of variables and questions
										
											7.1 Types of variables
										
											7.2 Types of questions
										
											8. Measurement errors associated with the questionnaire
										
											8.1 Measurement error associated with the questionnaire
										
											8.2 Recommendations to reduce measurement errors
										
											9. Questionnaire presentation and pretest
										
											9.1 Questionnaire presentation
										
											9.2 Layout of the online method
										
											9.3 Questionnaire pretest
										
											10. Production
										
											10.1 Production phase
										
											10.2 Selection and training of the survey team
										
											10.3 Measurement errors associated with the survey team
										
											10.4 Fieldwork
										
											10.5 Supervision and control of fieldwork
										
											10.6 Non- response
										
											Module3: Analysis and presentation of results
										
											11. Data preparation
										
											11.1 Data preparation for analysis
										
											11.2 Analysis of survey data
										
											11.3 Report and presentation of results
										
											12. Official statistics

In this subject, the use of Artificial Intelligence (AI) technologies is allowed as an integral part of the development of the work, provided that the final result reflects a significant contribution of the studentin the analysis and personal reflection. 
The student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the final result of the activity. 
The lack of transparency in the use of AI will be considered a lack of academic honesty and may lead to a penalty in the grade of the activity, or greater sanctions in serious cases.