Chat with us, powered by LiveChat Tricia's underlying point of her talk was that even with all this quantitative data and statistical analysis techniques, it still does not tell us everything. Sometimes richer (or deeper) da - EssayAbode

Tricia’s underlying point of her talk was that even with all this quantitative data and statistical analysis techniques, it still does not tell us everything. Sometimes richer (or deeper) da

Watch (or read the transcript of) the following TedTalk: The human insights missing from big data by Tricia Wang. Then, respond to the questions below:

  • Tricia's underlying point of her talk was that even with all this quantitative data and statistical analysis techniques, it still does not tell us everything. Sometimes richer (or deeper) data is needed. Why do you think we still need the human element in order to understand and make the best predictions/decisions?
  • As a manager, what do you think will be your best process for making decisions that balances the messages in qualitative (or deep) and quantitative data?

To receive full credit, your initial response should:

  • be a minimum of 300 words in length and are worth 8 points
  • demonstrate an understanding of key concepts;
  • include a rationale, evidence, or example that supports your response;
  • be free of significant mechanical errors. 
  • include a minimum of 1 scholarly source; referenced at the end of your post and cited within the text of your response according to APA 7th edition guidelines.

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