This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan. Furthermore this course will provide you with a general framework that allows you to not only understand each step required for a successful data collection and analysis, but also help you to identify errors associated with different data sources. You will learn some metrics to quantify each potential error, and thus you will have tools at hand to describe the quality of a data source. Finally we will introduce different large scale data collection efforts done by private industry and government agencies, and review the learned concepts through these examples. This course is suitable for beginners as well as those that know about one particular data source, but not others, and are looking for a general framework to evaluate data products.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Survey Data Collection and Analytics
Framework for Data Collection and Analysis
von
11,978 Angemeldet
Über diesen Kurs
7,109 recent views
Kompetenzen, die Sie erwerben
Data CollectionData QualityData AnalysisData Generating Process
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
13 Stunden zum Abschließen
Research Designs and Data Sources
The first course in the specialization provides an overview of the topics to come. This module walks you through the process of data collection and analysis. Starting with a research question and a review of existing data sources, we cover survey data collection techniques, highlight the importance of data curation, and discuss some basic features that can affect your data analysis when dealing with sample data. Issues of data access and resources for access are introduced in this module.
9 Videos (Gesamt 51 min), 5 Lektüren, 1 Quiz
9 Videos
Types of Data9m
Examples of Found Data2m
Visualizing the Data Generation Process5m
Data Curation5m
Data Analysis5m
Access Issues3m
Access Resources3m
Summary58
5 Lektüren
Course Overview10m
Readings and Resources List10m
Handouts10m
AAPOR (2015)40m
Couper (2013)30m
1 praktische Übung
Quiz for Week 120m
Woche
22 Stunden zum Abschließen
Measurements and Analysis Plan
In this module we will emphasize the importance of having a well-specified research question and analysis plan. We will provide an overview over the various data collection strategies, a variety of available modes for data collection and some thinking on how to choose the right mode.
6 Videos (Gesamt 36 min), 2 Lektüren, 1 Quiz
6 Videos
Planning on What You Want to Observe7m
Planning on How to Collect Data6m
New Modes4m
Web and Google6m
Choosing a Mode4m
2 Lektüren
Handouts10m
Jäckle et al. (2015)30m
1 praktische Übung
Quiz for Week 220m
Woche
32 Stunden zum Abschließen
Quality Framework
In this module you will be introduced to a general framework that allows you to not only understand each step required for a successful data collection and analysis, but also helps you to identify errors associated with different data sources. You will learn some metrics to quantify each potential error, and thus you will have tools at hand to describe the quality of a data source.
8 Videos (Gesamt 49 min), 3 Lektüren, 1 Quiz
8 Videos
Inference4m
Survey Life Cycle from a Design Perspective - Measurement4m
Survey Life Cycle from a Design Perspective - Representation5m
Survey Lifecycle from a Process Perspective1m
Survey Lifeycle from a Quality Perspective14m
Survey Lifecycle from a Quality Perspective (II) - Metrics4m
Survey Lifecycle from a Quality Perspective (III) - Coverage and Sampling8m
3 Lektüren
Handouts10m
Groves (2011)20m
Groves & Lyberg (2010)30m
1 praktische Übung
Quiz for Week 320m
Woche
42 Stunden zum Abschließen
Application of TSE Framework to Existing Surveys
In this module we introduce a few surveys across a variety of topics. For each we highlight data collection features. The surveys span a variety of topics. We challenge you to think about alternative data sources that can be used to gather the same information or insights.
8 Videos (Gesamt 36 min), 2 Lektüren, 1 Quiz
2 Lektüren
Handouts10m
Davidov (2008)30m
1 praktische Übung
Quiz for Week 420m
29%
nahm einen neuen Beruf nach Abschluss dieser Kurse auf
24%
ziehen Sie für Ihren Beruf greifbaren Nutzen aus diesem Kurs
Top-Bewertungen
Very clear and organised structure\n\nClear examples to support learning objectives\n\nAttractive use of voice\n\nOne point for improvement: Do not film while the lecturer is still refinding breath
Excelente curso, genera las herramientas necesarias para la recoleccion, transformacion, analisis e interpretacion de datos que requiero como principiante en este proceso
Dozenten
Frauke Kreuter, Ph.D.
Professor, Joint Program in Survey MethodologyAdjunct Research Professor, Institute for Social Research
Mariel Leonard
LecturerJoint Program in Survey Methodology
Über University of Maryland, College Park
The University of Maryland is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of the national academies and scores of Fulbright scholars. The institution has a $1.8 billion operating budget, secures $500 million annually in external research funding and recently completed a $1 billion fundraising campaign.
Über die Spezialisierung 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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