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.
This course is part of the Survey Data Collection and Analytics Specialization
Framework for Data Collection and Analysis
Offered By
About this Course
4.1
280 ratings
Skills you will gain
Data CollectionData QualityData AnalysisData Generating Process
Syllabus - What you will learn from this course
Week
13 hours to complete
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 (Total 51 min), 5 readings, 1 quiz
9 videos
Types of Data9m
Examples of Found Data2m
Visualizing the Data Generation Process5m
Data Curation5m
Data Analysis5m
Access Issues3m
Access Resources3m
Summary58s
5 readings
Course Overview10m
Readings and Resources List10m
Handouts10m
AAPOR (2015)40m
Couper (2013)30m
1 practice exercise
Quiz for Week 120m
Week
22 hours to complete
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 (Total 36 min), 2 readings, 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 readings
Handouts10m
Jäckle et al. (2015)30m
1 practice exercise
Quiz for Week 220m
Week
32 hours to complete
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 (Total 49 min), 3 readings, 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 readings
Handouts10m
Groves (2011)20m
Groves & Lyberg (2010)30m
1 practice exercise
Quiz for Week 320m
Week
42 hours to complete
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 (Total 36 min), 2 readings, 1 quiz
2 readings
Handouts10m
Davidov (2008)30m
1 practice exercise
Quiz for Week 420m
4.1
68 Reviews29%
started a new career after completing these courses
27%
got a tangible career benefit from this course
Top Reviews
By MM•Mar 7th 2018
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
By KM•Oct 5th 2018
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.
Instructors
Frauke Kreuter, Ph.D.
Professor, Joint Program in Survey MethodologyAdjunct Research Professor, Institute for Social Research
Mariel Leonard
LecturerJoint Program in Survey Methodology
About 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.
About the Survey Data Collection and Analytics Specialization
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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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