Data Science

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I'm learning data science techniques, refreshing my knowledge of statistics and restarting with python code.

  1. setup development environment
  2. open access data collection
  3. EDA
  4. after data and plots: central theorem
  5. test hypothesis
  6. test other correlations

Often assumptions are used in discussions, which are not justified by figures. The climate crisis is (unfortunately) a good example: it is often claimed by climate critics in a high tone of voice, that global warming is within the margins of our climate - just as warm summers have always been exceptional, but not impossible. Without further substantiation or data... but many things are not 100% certain At 95% or 99% probability based on data, there is plenty of reason for further investigation. Many recent publications have given prominence to further explanation of what 95% and 99% probability means in practice.