Module 4: Dealing With Data

Name: Module 4: Dealing With Data
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Some facts are simple and easy to search for online. But some content creators (e.g., nonfiction writers, news reporters, and podcasters) draw their information from complex data sources, including government reports, surveys, or technical journals. As such, fact-checking their writing isn’t as simple! Understanding how to navigate, analyze, and understand data sets and in-depth sources is essential for those who want to specialize or access the widest span of work as a fact-checker.

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3 Detailed Lessons

1 Knowledge Review Quiz

1 Hands-On Exercise

How This Module Works

In this module, you’ll learn how to work confidently with complex data. We’ll guide you through different types of data sources – from surveys to technical reports – and show you how to evaluate their credibility and relevance. With step-by-step guidance, case studies, and practical exercises, you’ll soon be able to assess claims backed by numbers and uncover what the data really says.

4.1: Fact-Checking Data: Overview

Gain an understanding of different types of data and which sources are most often used by content creators. Plus, explore the concepts of limitations and biases to help you develop a critical eye.

4.2: Fact-Checking Data: Process

Learn and practice a step-by-step fact-checking system by working along with a case study. Then put it into action with a practical exercise.

4.3: Module Quiz

Check what you’ve absorbed from the lessons with this no-pressure quiz.

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Why Is It Important to Fact-Check Data-Based Content?

Facts, figures, and statistics lend credence to the claims made in a piece of content. But what if the data has been misread or even misrepresented?

Working with data takes more than just number-crunching – it’s about knowing where information comes from and how it’s used. This means understanding how to navigate complex data sets, review the reliability of sources, and come to informed, logical conclusions. A fact-checker can get to the truth of the matter, clearing up mistakes to ensure the final published content accurately reflects the data.