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Data Science Questions and Hypotheses

Video Description

Why does a data scientist need to ask questions? How are questions essential in forming your strategy in a data science project? What are hypotheses and how are they formed? How do you go about testing a hypothesis? These questions and more are tackled in this video, along with some supplementary information about the data science process and the various subtleties of the craft that no artificial intelligence, no matter how sophisticated, can tackle (at least for the time being).

We will cover:
  • The importance of questions in data science
  • The limitations of artificial intelligence in its contribution to data science
  • How the human factor can enhance the data science process by complementing the tools we use
  • The value of hypotheses in data science
  • The types of questions we ask in data science
  • Forming a hypothesis
  • Proving and disproving a hypothesis
  • Constructing an experiment to test a hypothesis
  • Evaluating the experimental results
  • Answering a question with confidence
  • Sensitivity analysis
  • Big Data to the rescue and the value of careful sampling

Table of Contents

  1. Data Science Questions and Hypotheses 00:31:01