Framework for Data Collection and Analysis

Framework for Data Collection and Analysis

This course is part of Survey Data Collection and Analytics Specialization

Instructors: Frauke Kreuter, Ph.D.

Access provided by Mojatu Foundation

35,936 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

773 reviews

Intermediate level

Some related experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

93%

Most learners liked this course

4 modules

Gain insight into a topic and learn the fundamentals.

773 reviews

Intermediate level

Some related experience required

Flexible schedule

1 week at 10 hours a week

Learn at your own pace

93%

Most learners liked this course

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

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

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

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.

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.

What's included

9 videos5 readings1 assignment2 discussion prompts

9 videos Total 51 minutes

Research Question Design 14 minutes
Types of Data 9 minutes
Examples of Found Data 3 minutes
Visualizing the Data Generation Process 6 minutes
Data Curation 6 minutes
Data Analysis 6 minutes
Access Issues 3 minutes
Access Resources 4 minutes
Summary 1 minute

5 readings Total 100 minutes

Course Overview 10 minutes
Readings and Resources List 10 minutes
Handouts 10 minutes
AAPOR (2015) 40 minutes
Couper (2013) 30 minutes

1 assignment Total 30 minutes

Quiz for Week 1 30 minutes

2 discussion prompts Total 20 minutes

Discussion Prompt: Your own experience 10 minutes
Discussion Prompt: Privacy 10 minutes

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.

What's included

6 videos2 readings1 assignment

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.

What's included

8 videos3 readings1 assignment

8 videos Total 49 minutes

Quality of Data 5 minutes
Inference 4 minutes
Survey Life Cycle from a Design Perspective - Measurement 5 minutes
Survey Life Cycle from a Design Perspective - Representation 5 minutes
Survey Lifecycle from a Process Perspective 2 minutes
Survey Lifeycle from a Quality Perspective 15 minutes
Survey Lifecycle from a Quality Perspective (II) - Metrics 4 minutes
Survey Lifecycle from a Quality Perspective (III) - Coverage and Sampling 9 minutes

3 readings Total 60 minutes

Handouts 10 minutes
Groves (2011) 20 minutes
Groves & Lyberg (2010) 30 minutes

1 assignment Total 30 minutes

Quiz for Week 3 30 minutes

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.

What's included

8 videos2 readings1 assignment2 discussion prompts

8 videos Total 36 minutes

NCVS 8 minutes
NSDUH 3 minutes
SCA 4 minutes
NAEP 3 minutes
BRFSS 3 minutes
CES 3 minutes
SHARE 5 minutes
ESS 7 minutes

2 readings Total 40 minutes

Handouts 10 minutes
Davidov (2008) 30 minutes

1 assignment Total 30 minutes

Quiz for Week 4 30 minutes

2 discussion prompts Total 20 minutes

Discussion Prompt: Alternative Data Sources 10 minutes
Discussion prompt: In your country 10 minutes

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

Instructor ratings

(156 ratings)

Frauke Kreuter, Ph.D.

University of Maryland, College Park

4 Courses 67,296 learners

Offered by

University of Maryland, College Park

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

5 stars
54.98%
4 stars
25.22%
3 stars
11.90%
2 stars
4.01%
1 star
3.88%

Showing 3 of 773

Reviewed on Feb 25, 2022

The course have helped me a lot to improve my Data collection skills and i have learned a lot of things that is going to help me in teh future to collect my data properly.

Reviewed on Oct 30, 2020

Useful to build basic knowledge which helps you choosing a better mode and linking the objectives of research with the tools (how).Thanks to the instructor and Coursera.

Reviewed on Dec 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.

View more reviews