See attached files.
Original question:
After reading the required article and watching the video, share your thoughts on ONE of the following two questions:
(1) Based on the case of Google Flu Trends, explain why “correlation does not equal causation”. While it is difficult to fully prove causation, what are the basic questions that HR professionals should consider when making a logical, causal case?
[Hints: messy data and sampling bias, as discussed by N. Diakopoulous]
(2) What lessons can we learn from the failure of the Google Flu Trends project?
[Hints: Do big data complement or supplement traditional data? Is big data always better data? ]
Please make the post substantive. Dnt just say I agree with you. Add a new perspective to the discussion