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.

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.
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Reviewed on Aug 17, 2021
I learnt new things about surveys, data collection, usage of data collected and the examples of surveys was quite useful. The course gave me added knowledge.
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 Jun 7, 2016
The deliver papers are great but slides are poor. In overall, a good course to begin learning about Data Collection and Analysis.
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