This course is part of the Survey Data Collection and Analytics Specialization

4.2
stars
703 ratings

Frauke Kreuter, Ph.D. +1 more instructor

27,941 already enrolled

Offered By

Survey Data Collection and Analytics SpecializationUniversity of Maryland, College Park

About this Course

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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.

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 1 of 7 in the

Survey Data Collection and Analytics Specialization

Intermediate Level

Approx. 9 hours to complete

English

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Skills you will gain

Data Collection
Data Quality
Data Analysis
Data Generating Process

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 7 in the

Survey Data Collection and Analytics Specialization

Intermediate Level

Approx. 9 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.17/5 (134 Ratings)

Frauke Kreuter, Ph.D.

Professor, Joint Program in Survey Methodology

Adjunct Research Professor, Institute for Social Research

54,775 Learners

4 Courses

Mariel Leonard

Lecturer

Joint Program in Survey Methodology

27,941 Learners

1 Course

Offered by

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.

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Syllabus - What you will learn from this course

Content Rating93%(2,199 ratings)

Week1

Week 1

3 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.

3 hours to complete

9 videos (Total 51 min), 5 readings, 1 quiz

Week2

Week 2

2 hours to complete

Measurements and Analysis Plan

2 hours to complete

6 videos (Total 36 min), 2 readings, 1 quiz

Week3

Week 3

2 hours to complete

Quality Framework

2 hours to complete

8 videos (Total 49 min), 3 readings, 1 quiz

8 videos

Quality of Data5mInference4mSurvey Life Cycle from a Design Perspective - Measurement4mSurvey Life Cycle from a Design Perspective - Representation5mSurvey Lifecycle from a Process Perspective1mSurvey Lifeycle from a Quality Perspective14mSurvey Lifecycle from a Quality Perspective (II) - Metrics4mSurvey Lifecycle from a Quality Perspective (III) - Coverage and Sampling8m

3 readings

Handouts10mGroves (2011)20mGroves & Lyberg (2010)30m

1 practice exercise

Quiz for Week 330m

Week4

Week 4

2 hours to complete

Application of TSE Framework to Existing Surveys

2 hours to complete

8 videos (Total 36 min), 2 readings, 1 quiz

Reviews

4.2

161 reviews

5 stars
54.05%
4 stars
25.60%
3 stars
12.51%
2 stars
3.84%
1 star
3.98%

TOP REVIEWS FROM FRAMEWORK FOR DATA COLLECTION AND ANALYSIS

by SAAug 10, 2016

Great overview of the survey process. Instructor presented information in a concise manner. Highly recommended.

by MIDec 30, 2021

The way the instructor was teaching was not very exciting, but the course was a good start as it had general information about data analysis.

by MHFeb 21, 2021

Lot of definitions, so some of the questions (especially week 4) test reading comprehension more than understanding - but hopefully this will improve in the subsequent courses of the specialization.

by MMMar 6, 2018

Very clear and organised structure

Clear examples to support learning objectives

Attractive use of voice

One point for improvement: Do not film while the lecturer is still refinding breath

View all reviews

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?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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.
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.

More questions? Visit the Learner Help Center.

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Framework for Data Collection and Analysis

About this Course

Skills you will gain