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Data Science Through the Lens of Journalism

In many ways, data science is a natural extension of journalism. Traditionally, reporters would conduct a number of interviews and use a qualitative approach to craft a story. Similarly, data scientists look at a set of quantitative information, ask questions via numerical analysis, and tease out a narrative arc.

This session will include a brief overview of the architecture of data science, explain what constitutes big data, describe the questions that data scientists ask, review some basic statistical concepts and how to compute them, and describe some of the ways in which people use statistics for nefarious purposes.

Presented by a former journalist/ current data scientist/ lifelong math lover, it a somewhat subjective take on what a journalist needs to know about data science and basic statistics. Audience members will not be subjected to an excess equations; the approach to explaining these concepts is primarily visual and heavily informed by Childcraft Encyclopedias.

Questions Answered

  1. How are data science and journalism related?
  2. What is the framework used to support data science? (Technical infrastructure, brief explanation of the internet through pictures)
  3. What are the basic statistical concepts that a journalist would want to understand?
  4. What constitutes big data?
  5. How does a statistician look at a graph? When confronted with data or statistics, which questions should we be asking?

Speakers

Organizer

Zanab Hussain SimpleReach


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