About 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.

Created by: University of Maryland, College Park

Taught by: Frauke Kreuter, Ph.D., Professor, Joint Program in Survey Methodology
Adjunct Research Professor, Institute for Social Research
Taught by: Mariel Leonard

Basic Info	Course 1 of 7 in the Survey Data Collection and Analytics Specialization.
Level	Intermediate
Commitment	4 weeks of study, 1-2 hours/week
Language	English
How To Pass	Pass all graded assignments to complete the course.
User Ratings	4.1 stars Average User Rating 4.1See what learners said

Syllabus

WEEK 1

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 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.

9 videos, 5 readings

Reading: Course Overview
Reading: Readings and Resources List
Video: Research Question Design
Discussion Prompt: Discussion Prompt: Your own experience
Video: Types of Data
Video: Examples of Found Data
Video: Visualizing the Data Generation Process
Video: Data Curation
Video: Data Analysis
Video: Access Issues
Video: Access Resources
Video: Summary
Discussion Prompt: Discussion Prompt: Privacy
Reading: Handouts
Reading: AAPOR (2015)
Reading: Couper (2013)

Graded: Quiz for Week 1

WEEK 2

Measurements and Analysis Plan

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.

6 videos, 2 readings

Video: Issues with Inductive Reasoning
Video: Planning on What You Want to Observe
Video: Planning on How to Collect Data
Video: New Modes
Video: Web and Google
Video: Choosing a Mode
Reading: Handouts
Reading: Jäckle et al. (2015)

Graded: Quiz for Week 2

WEEK 3

Quality Framework

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 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.

8 videos, 3 readings

Video: Quality of Data
Video: Inference
Video: Survey Life Cycle from a Design Perspective - Measurement
Video: Survey Life Cycle from a Design Perspective - Representation
Video: Survey Lifecycle from a Process Perspective
Video: Survey Lifeycle from a Quality Perspective
Video: Survey Lifecycle from a Quality Perspective (II) - Metrics
Video: Survey Lifecycle from a Quality Perspective (III) - Coverage and Sampling
Reading: Handouts
Reading: Groves (2011)
Reading: Groves & Lyberg (2010)

Graded: Quiz for Week 3

WEEK 4

Application of TSE Framework to Existing Surveys

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.

8 videos, 2 readings

Video: NCVS
Video: NSDUH
Video: SCA
Video: NAEP
Video: BRFSS
Video: CES
Discussion Prompt: Discussion Prompt: Alternative Data Sources
Video: SHARE
Video: ESS
Discussion Prompt: Discussion prompt: In your country
Reading: Handouts
Reading: Davidov (2008)

Graded: Quiz for Week 4

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Creators

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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Ratings and Reviews

Rated 4.1 out of 5 of 124 ratings

Awesome course,awesome presenter!

I thought it had just the right level of detail for a foundation course.

thank you

Great overview of designed and organic data collection! I feel more confident interpreting and understanding survey results and providing input on community-based research projects. Some of the readings were challenging for me because I have not studied statistics, but it was a welcome challenge. I plan to return to some of the course materials after completing a stats 101 course.

I took the survey questionnaire design course in this specialization two years ago and I wish I'd taken this first. If you're thinking of sampling courses from this specialization, I highly recommend you start here.

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Framework for Data Collection and Analysis

Framework for Data Collection and Analysis

Framework for Data Collection and Analysis