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.
Este curso faz parte do Programa de cursos integrados Survey Data Collection and Analytics
Framework for Data Collection and Analysis
oferecido por
Programa de cursos integrados Survey Data Collection and Analytics Universidade de Maryland, College Park
Informações sobre o curso
4.2
301 classificações
Habilidades que você terá
Data CollectionData QualityData AnalysisData Generating Process
Programa - O que você aprenderá com este curso
Semana
13 horas para concluir
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 vídeos (total de (Total 51 mín.) min), 5 leituras, 1 teste
9 videos
Types of Data9min
Examples of Found Data2min
Visualizing the Data Generation Process5min
Data Curation5min
Data Analysis5min
Access Issues3min
Access Resources3min
Summary58s
5 leituras
Course Overview10min
Readings and Resources List10min
Handouts10min
AAPOR (2015)40min
Couper (2013)30min
1 exercício prático
Quiz for Week 120min
Semana
22 horas para concluir
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 vídeos (total de (Total 36 mín.) min), 2 leituras, 1 teste
6 videos
Planning on What You Want to Observe7min
Planning on How to Collect Data6min
New Modes4min
Web and Google6min
Choosing a Mode4min
2 leituras
Handouts10min
Jäckle et al. (2015)30min
1 exercício prático
Quiz for Week 220min
Semana
32 horas para concluir
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 vídeos (total de (Total 49 mín.) min), 3 leituras, 1 teste
8 videos
Quality of Data5min
Inference4min
Survey Life Cycle from a Design Perspective - Measurement4min
Survey Life Cycle from a Design Perspective - Representation5min
Survey Lifecycle from a Process Perspective1min
Survey Lifeycle from a Quality Perspective14min
Survey Lifecycle from a Quality Perspective (II) - Metrics4min
Survey Lifecycle from a Quality Perspective (III) - Coverage and Sampling8min
3 leituras
Handouts10min
Groves (2011)20min
Groves & Lyberg (2010)30min
1 exercício prático
Quiz for Week 320min
Semana
42 horas para concluir
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 vídeos (total de (Total 36 mín.) min), 2 leituras, 1 teste
2 leituras
Handouts10min
Davidov (2008)30min
1 exercício prático
Quiz for Week 420min
29%
comecei uma nova carreira após concluir estes cursos
24%
consegui um benefício significativo de carreira com este curso
Melhores avaliações
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
The teacher for the course was great. She explained everything very clearly. She also explained what is coming next. Learned a lot. Reading materials were overwhelming.
Instrutores
Frauke Kreuter, Ph.D.
Professor, Joint Program in Survey MethodologyAdjunct Research Professor, Institute for Social Research
Mariel Leonard
LecturerJoint Program in Survey Methodology
Sobre Universidade de 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.
Sobre o Programa de cursos integrados 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.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Qual é a política de reembolso?
Existe algum auxílio financeiro disponível?
Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.
O Coursera proporciona acesso universal à melhor educação do mundo fazendo parcerias com as melhores universidades e organizações para oferecer cursos on-line.
© 2019 Coursera Inc. Todos os direitos reservados.
