This course presents research conducted to increase our understanding of how data collection decisions affect survey errors. This is not a “how–to-do-it” course on data collection, but instead reviews the literature on survey design decisions and data quality in order to sensitize learners to how alternative survey designs might impact the data obtained from those surveys.
Ce cours fait partie de la Spécialisation Survey Data Collection and Analytics
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Spécialisation Survey Data Collection and Analytics Université du MichiganÀ propos de ce cours
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Résultats de carrière des étudiants
50%
ont commencé une nouvelle carrière après avoir terminé ce cours
33%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
40%
a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 2 sur 7 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau débutant
Approx. 15 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université du Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Programme du cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
Module 1: Introduction, Classic Modes of Survey Data Collection
In this lesson, you will be introduced to some key concepts about survey data collection methods that we will rely on throughout the course. By the end of this lesson, you should be well acquainted with the major sources of survey error and how these are affected -- usually in the form of tradeoffs -- by the particular mode used to administer questions and capture responses.
3 heures pour terminer
12 vidéos (Total 134 min), 5 lectures, 1 quiz
12 vidéos
1.2.1 Introduction to Survey Errors10 min
1.2.2 Variable Error and Bias10 min
1.2.3 Total Survey Error7 min
1.3.1 What do we mean by “mode?”16 min
1.3.2 Mode Choice (by respondent)12 min
1.4.1 Mixed Mode Design8 min
1.4.2 Concurrent Mixed Mode8 min
1.4.3 Sequential (Follow-up) Mixed Mode11 min
1.4.4 Interview with David Weir (U. Michigan) on Mixed Mode Designs15 min
1.5.1 Response Rates6 min
1.5.2 Nonresponse Error13 min
5 lectures
Module 1 Overview10 min
Help us learn more about you!10 min
Module 1 Required Readings10 min
Module 1 Lecture Slides10 min
Notice for Auditing Learners: Assignment Submission10 min
1 exercice pour s'entraîner
Module 1: Classic Modes of Data Collection20 min
3 heures pour terminer
Module 2: Self-administration, Online Data Collection
This second lesson focuses on modes in which survey respondents self-administer questions and provide their responses directly to researchers. By the end of Lesson 2, you will understand the pros and cons of self-administered modes from the TSE perspective.
3 heures pour terminer
9 vidéos (Total 131 min), 3 lectures, 1 quiz
9 vidéos
2.1.2 ACASI continued8 min
2.2.1 Coverage17 min
2.2.2 Nonresponse9 min
2.2.3 Measurement21 min
2.3.1 Progress Indicators, Running Tallies10 min
2.3.2 Online Definitions6 min
2.3.3 Speeding Interventions10 min
2.4 Reg Baker (MRII) about web surveys in market research36 min
3 lectures
Module 2 Overview10 min
Module 2 Required Readings10 min
Module 2 Lecture Slides10 min
1 exercice pour s'entraîner
Quiz Two24 min
4 heures pour terminer
Module 3: Interviewers and Interviewing
In this lesson, we explore the various roles interviewers take on beside asking questions and collecting answers, as well as some of the different approaches to interviewing that have been proposed and how they affect the accuracy of responses. By the end of Lesson 3, you will appreciate the benefits and costs of collecting data in interviews and will be able to contrast them with the costs and benefits of self-administration.
4 heures pour terminer
9 vidéos (Total 173 min), 3 lectures, 1 quiz
9 vidéos
3.1.2 Respondent selection, Within Household Sampling14 min
3.1.3 Proxy Responding13 min
3.2.1 Standardization Debate: Wording vs. Meaning12 min
3.2.2 Different approaches to standardized interviewing14 min
3.2.3 Personal vs. Formal Style, I-R Rapport18 min
3.3.1 Variance: Interviewer Behavior25 min
3.3.2 Bias: Interviewers’ Fixed Attributes16 min
3.4 Interview with Nora Cate Schaeffer (UW) about recruitment and interviewing40 min
3 lectures
Module 3 Overview10 min
Module 3 Required Readings10 min
Module 3 Lecture Slides10 min
1 exercice pour s'entraîner
Quiz Three20 min
5 heures pour terminer
Module 4: Emerging modes, new data sources
In this lesson, we focus on some new data collection modes such as mobile web surveys and SMS text interviews, as well as alternative data sources such as sensor data, administrative data, and social media. By the end of this lesson, you will have a sense of the issues to which survey methodologists and survey researchers are devoting much of their attention these days. You will be able to weigh the pros and cons of these new methods and data sources.
5 heures pour terminer
12 vidéos (Total 194 min), 4 lectures, 2 quiz
12 vidéos
4.1.2 Mobile Web Surveys19 min
4.1.3 Text Message Surveys11 min
4.1.4 Text vs. Voice Interviews15 min
4.2.1 Record linkage: statistical issues12 min
4.2.2 Record linkage: Techniques18 min
4.2.3 Record linkage: informed consent and ethical issues12 min
4.3.1 Uses of Big Data, Sensing Technology, Social Media Content as Data17 min
4.3.2 Social media applications: Measuring Mood and Depression11 min
4.3.3 Social Media and Population Estimates: Successes7 min
4.3.4 Why does social media content align with surveys data sometimes and not other times?13 min
4.4 Interview with Aigul Mavletova (National Research University Higher School of Economics, Mosow) on mobile web surveys37 min
4 lectures
Module 4 Overview10 min
Module 4 Required Readings10 min
Module 4 Lecture Slides10 min
Post-course Survey10 min
2 exercices pour s'entraîner
Module 4: Emerging modes, new data sources20 min
Final Exam40 min
Avis
Meilleurs avis pour DATA COLLECTION: ONLINE, TELEPHONE AND FACE-TO-FACE
par J26 mai 2019
- the difference between mobile survey and web survey\n\ndifference between online and face to face interviews\n\ndifference between telephone interviews and computer interviws
par SK19 juil. 2016
There is one word for this Course "Amazing". No matter if you are a undergrad student or a seasoned researcher, you'll feel that you have learned a lot from this course.
par CP28 mars 2017
The course material presents the traditional methods and latest developments in data collection for survey research. Excellent overall.
par MN14 août 2018
This course thought me exactly what i was expecting, the course lecturer is amazing and know exactly who make his student understand.
À propos du Spécialisation Survey Data Collection and Analytics
This specialization covers the fundamentals of surveys as used in market research, evaluation research, social science and political research, official government statistics, and many other topic domains. In six courses, you will learn the basics of questionnaire design, data collection methods, sampling design, dealing with missing values, making estimates, combining data from different sources, and the analysis of survey data. In the final Capstone Project, you’ll apply the skills learned throughout the specialization by analyzing and comparing multiple data sources.
Faculty for this specialisation comes from the Michigan Program in Survey Methodology and the Joint Program in Survey Methodology, a collaboration between the University of Maryland, the University of Michigan, and the data collection firm Westat, founded by the National Science Foundation and the Interagency Consortium of Statistical Policy in the U.S. to educate the next generation of survey researchers, survey statisticians, and survey methodologists. In addition to this specialization we offer short courses, a summer school, certificates, master degrees as well as PhD programs.
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