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Framework for Data Collection and Analysis

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Framework for Data Collection and Analysis

This course is part of Survey Data Collection and Analytics Specialization

Instructors: Frauke Kreuter, Ph.D.

36,549 already enrolled

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

774 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.

774 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

91% of learners achieved a positive career outcome

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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.

Module details

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 videosTotal 51 minutes

Research Question Design14 minutes
Types of Data9 minutes
Examples of Found Data3 minutes
Visualizing the Data Generation Process6 minutes
Data Curation6 minutes
Data Analysis6 minutes
Access Issues3 minutes
Access Resources4 minutes
Summary1 minute

5 readingsTotal 100 minutes

Course Overview10 minutes
Readings and Resources List10 minutes
Handouts10 minutes
AAPOR (2015)40 minutes
Couper (2013)30 minutes

1 assignmentTotal 30 minutes

Quiz for Week 130 minutes

2 discussion promptsTotal 20 minutes

Discussion Prompt: Your own experience10 minutes
Discussion Prompt: Privacy10 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 videosTotal 49 minutes

Quality of Data5 minutes
Inference4 minutes
Survey Life Cycle from a Design Perspective - Measurement5 minutes
Survey Life Cycle from a Design Perspective - Representation5 minutes
Survey Lifecycle from a Process Perspective2 minutes
Survey Lifeycle from a Quality Perspective15 minutes
Survey Lifecycle from a Quality Perspective (II) - Metrics4 minutes
Survey Lifecycle from a Quality Perspective (III) - Coverage and Sampling9 minutes

3 readingsTotal 60 minutes

Handouts10 minutes
Groves (2011)20 minutes
Groves & Lyberg (2010)30 minutes

1 assignmentTotal 30 minutes

Quiz for Week 330 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 videosTotal 36 minutes

NCVS8 minutes
NSDUH3 minutes
SCA4 minutes
NAEP3 minutes
BRFSS3 minutes
CES3 minutes
SHARE5 minutes
ESS7 minutes

2 readingsTotal 40 minutes

Handouts10 minutes
Davidov (2008)30 minutes

1 assignmentTotal 30 minutes

Quiz for Week 430 minutes

2 discussion promptsTotal 20 minutes

Discussion Prompt: Alternative Data Sources10 minutes
Discussion prompt: In your country10 minutes

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Instructors

Instructor ratings

(156 ratings)

Frauke Kreuter, Ph.D.

University of Maryland, College Park

4 Courses68,132 learners

Offered by

University of Maryland, College Park

Learner reviews

5 stars
55.09%
4 stars
25.16%
3 stars
11.87%
2 stars
4%
1 star
3.87%

Showing 3 of 774

Reviewed on Aug 22, 2017

This great course and a good foundation for the specialization. The lecturer is amazing and experienced. I really enjoyed this one.

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.

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