Is this course really 100% online? Do I need to attend any classes in person?

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.

Can I just enroll in a single course?

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. 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.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. 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. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

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.

Survey Data Collection and Analytics Specialization

Survey Data Collection and Analytics Specialization

Collect and analyze data, and communicate results. Learn to collect quality data and conduct insightful data analysis in six courses.

Instructors: Mariel Leonard

22,945 already enrolled

Included with Coursera Plus

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6 course series

Get in-depth knowledge of a subject

4.3

(901 reviews)

Beginner level

No prior experience required

3 months to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 course series

Get in-depth knowledge of a subject

4.3

(901 reviews)

Beginner level

No prior experience required

3 months to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Understand the basics of survey design, sampling methods, data collection and data analysis
Apply the skills learned to analyze and compare multiple data sources in a capstone project

Details to know

Shareable certificate

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Taught in English

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Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from University of Michigan

Specialization - 6 course series

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.

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.

Framework for Data Collection and Analysis

Course 19 hours

What you'll learn

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.

Skills you'll gain

Category: Data Collection

Category: Sampling (Statistics)

Category: Big Data

Category: Surveys

Category: Data Analysis

Category: Data Validation

Category: Statistical Methods

Category: Research Design

Category: Data Quality

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

Course 221 hours

What you'll learn

Appricate and compare the pros and cons of self-administered modes and interviews
Explore the emerging modes and data sources such as mobile web surveys and social media data
Understand the key concepts about survey data collection methods

Skills you'll gain

Category: Data Collection

Category: Surveys

Category: Interviewing Skills

Category: Qualitative Research

Category: Text Mining

Category: Data Validation

Category: Unstructured Data

Category: Research Methodologies

Category: Data Quality

Category: Sampling (Statistics)

Questionnaire Design for Social Surveys

Course 316 hours

What you'll learn

Understand the basic elements of designing and evaluating questionnaires

Skills you'll gain

Category: Survey Creation

Category: Interviewing Skills

Category: Research Design

Category: Qualitative Research

Category: Research

Category: Data Collection

Category: Quantitative Research

Category: Research Methodologies

Sampling People, Networks and Records

Course 425 hours

What you'll learn

Understand the value and risks sampling and randomization methods bring to scientific investigation
Differentiate different types of sampling methods and their applications
Explain the principles and techniques of probability sampling methods

Skills you'll gain

Category: Sampling (Statistics)

Category: Network Analysis

Category: Sample Size Determination

Category: Data Collection

Category: Probability

Category: Statistical Methods

Category: Statistical Software

Category: Probability & Statistics

Category: Surveys

Category: Quantitative Research

Category: Statistical Analysis

Dealing With Missing Data

Course 517 hours

What you'll learn

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®.

Skills you'll gain

Category: Sampling (Statistics)

Category: Regression Analysis

Category: Statistical Methods

Category: Data Cleansing

Category: Data Quality

Category: Statistical Inference

Category: R (Software)

Category: Data Transformation

Category: STATA (Software)

Category: Statistical Software

Category: Data Analysis

Category: Statistical Analysis

Combining and Analyzing Complex Data

Course 69 hours

What you'll learn

In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.

Skills you'll gain

Category: Sampling (Statistics)

Category: Informed Consent

Category: Stata

Category: Regression Analysis

Category: Statistical Modeling

Category: Data Ethics

Category: Statistical Analysis

Category: Descriptive Statistics

Category: R (Software)

Category: STATA (Software)

Category: Data Integration

Category: R Programming

Category: Information Privacy

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Mariel Leonard

University of Maryland, College Park

1 Course34,825 learners

Frederick Conrad, Ph.D.

University of Michigan

4 Courses48,512 learners

James M Lepkowski

University of Michigan

3 Courses14,021 learners

Offered by

University of Michigan

University of Maryland, College Park

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Frequently asked questions

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.