About this Specialization
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Beginner Level

Beginner Level

Hours to complete

Approx. 6 months to complete

Suggested 5 hours/week
Available languages

English

Subtitles: English...

Skills you will gain

Data CollectionCluster SamplingR ProgrammingMissing Data
100% online courses

100% online courses

Start instantly and learn at your own schedule.
Flexible Schedule

Flexible Schedule

Set and maintain flexible deadlines.
Beginner Level

Beginner Level

Hours to complete

Approx. 6 months to complete

Suggested 5 hours/week
Available languages

English

Subtitles: English...

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 7 Courses in this Specialization

Course1

Framework for Data Collection and Analysis

4.1
267 ratings
67 reviews
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....
Course2

Data Collection: Online, Telephone and Face-to-face

4.5
136 ratings
30 reviews
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. The course reviews a range of survey data collection methods that are both interview-based (face-to-face and telephone) and self-administered (paper questionnaires that are mailed and those that are implemented online, i.e. as web surveys). Mixed mode designs are also covered as well as several hybrid modes for collecting sensitive information e.g., self-administering the sensitive questions in what is otherwise a face-to-face interview. The course also covers newer methods such as mobile web and SMS (text message) interviews, and examines alternative data sources such as social media. It concentrates on the impact these techniques have on the quality of survey data, including error from measurement, nonresponse, and coverage, and assesses the tradeoffs between these error sources when researchers choose a mode or survey design....
Course3

Questionnaire Design for Social Surveys

4.4
248 ratings
69 reviews
This course will cover the basic elements of designing and evaluating questionnaires. We will review the process of responding to questions, challenges and options for asking questions about behavioral frequencies, practical techniques for evaluating questions, mode specific questionnaire characteristics, and review methods of standardized and conversational interviewing....
Course4

Sampling People, Networks and Records

4.5
39 ratings
14 reviews
Good data collection is built on good samples. But the samples can be chosen in many ways. Samples can be haphazard or convenient selections of persons, or records, or networks, or other units, but one questions the quality of such samples, especially what these selection methods mean for drawing good conclusions about a population after data collection and analysis is done. Samples can be more carefully selected based on a researcher’s judgment, but one then questions whether that judgment can be biased by personal factors. Samples can also be draw in statistically rigorous and careful ways, using random selection and control methods to provide sound representation and cost control. It is these last kinds of samples that will be discussed in this course. We will examine simple random sampling that can be used for sampling persons or records, cluster sampling that can be used to sample groups of persons or records or networks, stratification which can be applied to simple random and cluster samples, systematic selection, and stratified multistage samples. The course concludes with a brief overview of how to estimate and summarize the uncertainty of randomized sampling....

Instructors

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Richard Valliant, Ph.D.

Research Professor
Joint Program in Survey Methodology
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Frauke Kreuter, Ph.D.

Professor, Joint Program in Survey Methodology
Adjunct Research Professor, Institute for Social Research
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Frederick Conrad, Ph.D.

Research Professor, Survey Methodology
Institute for Social Research
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James M Lepkowski

Research Professor
Survey Research Center, Institute for Social Research

Mariel Leonard

Lecturer
Joint 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 University of 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....

Frequently Asked Questions

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • All courses are on demand and available all the time. So it really depends how much time you have on your hand. You can certainly comfortably move through the specialization thinking of taking one course per month.

  • Introductory statistics knowledge does help, for the later courses.

  • The first course gives an overview over the topic and the framework with think in. But the courses can in principle be taken in any order. If you are looking for guidance we recommend to take at least the sampling Course (course 4) before the course on dealing with missing data (course 5).

  • If you completed the Questionnaire Design course previously and earned a Verified Certificate, you will automatically receive credit toward the Specialization for that course. Additionally, if you received a Verified Certificate and would like enroll for the specialization, the specialization cost will be automatically discounted to accommodate for the previous payment.

  • Learners who complete this specialization will know how to write questions, set-up good data collection, properly analyze survey data, draw samples, weight survey data and deal with missing values, and choose a proper survey mode. Completing the specialization will also help you prepare for a master's program and pivot your career to a rapidly evolving industry.

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