Separating hype from value

Separating hype from value >> A Crash Course in Data Science

The project isn’t designed to answer a concrete question.

Social media data has well known response biases

The Twitter API isn’t the best way to access social media data.

The project likely is not hype and will solve a critical problem.

http://archive.wired.com/science/discoveries/magazine/16-07/pb_theory/

One quote from the story is:

“There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.”

Which hype vs. reality question does this paragraph fail?

1 point

What is the question you are trying to answer with data?

If you could answer the question, could you use the answer?

Do you have the data to answer that question?

What is the question you are trying to answer with data?

If you could answer the question, could you use the answer?

Do you have the data to answer that question?

What is the question you are trying to answer with data?

If you could answer the question, could you use the answer?

Separating hype from value >> A Crash Course in Data Science

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